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Tag #classification

2687 papers:

EDMEDM-2019-KaserS #interactive #modelling #network #student
Exploring Neural Network Models for the Classification of Students in Highly Interactive Environments (TK, DLS).
EDMEDM-2019-MbouzaoDS #analysis #interactive #student #video
A Methodology for Student Video Interaction Patterns Analysis and Classification (BM, MCD, IS).
ICPCICPC-2019-SchnappingerOPF #learning #maintenance #predict #static analysis #tool support
Learning a classifier for prediction of maintainability based on static analysis tools (MS, MHO, AP, AF), pp. 243–248.
ICSMEICSME-2019-KallisSCP #machine learning
Ticket Tagger: Machine Learning Driven Issue Classification (RK, ADS, GC, SP), pp. 406–409.
ICSMEICSME-2019-MillsEBKCH #learning #traceability
Tracing with Less Data: Active Learning for Classification-Based Traceability Link Recovery (CM, JEA, AB, GK, SC, SH), pp. 103–113.
MSRMSR-2019-KiehnPC #empirical #using #version control
Empirical study in using version histories for change risk classification (MK, XP, FC), pp. 58–62.
SANERSANER-2019-NghiYJ #algorithm #dependence #network
Bilateral Dependency Neural Networks for Cross-Language Algorithm Classification (BDQN, YY, LJ), pp. 422–433.
CoGCoG-2019-SoaresB #behaviour
Deep Variational Autoencoders for NPC Behaviour Classification (ESS, VB), pp. 1–4.
CIKMCIKM-2019-0002CZTZG #graph #named
Meta-GNN: On Few-shot Node Classification in Graph Meta-learning (FZ0, CC, KZ, GT, TZ, JG), pp. 2357–2360.
CIKMCIKM-2019-AhmadvandSCA #named #topic
ConCET: Entity-Aware Topic Classification for Open-Domain Conversational Agents (AA, HS, JIC, EA), pp. 1371–1380.
CIKMCIKM-2019-CaoZXPY #adaptation #consistency #image #semantics
Adversarial Domain Adaptation with Semantic Consistency for Cross-Domain Image Classification (MC, XZ, YX, YP, BY), pp. 259–268.
CIKMCIKM-2019-ChenLX0 #network #sentiment
Sentiment Commonsense Induced Sequential Neural Networks for Sentiment Classification (SC, XL, YX, LH0), pp. 1021–1030.
CIKMCIKM-2019-FanBSL #fine-grained #network #prototype #scalability
Large Margin Prototypical Network for Few-shot Relation Classification with Fine-grained Features (MF, YB, MS, PL0), pp. 2353–2356.
CIKMCIKM-2019-GozuacikBBC #concept #detection
Unsupervised Concept Drift Detection with a Discriminative Classifier (ÖG, AB, HRB, FC), pp. 2365–2368.
CIKMCIKM-2019-GuoAWPC00 #multi #recognition
Multi-stage Deep Classifier Cascades for Open World Recognition (XG, AAF, LW, HP, XC0, KZ0, LZ0), pp. 179–188.
CIKMCIKM-2019-HuangCLCHLZZW #approach #multi #network
Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach (WH, EC, QL0, YC, ZH, YL, ZZ, DZ, SW), pp. 1051–1060.
CIKMCIKM-2019-HuangWZLC #network #prototype
Deep Prototypical Networks for Imbalanced Time Series Classification under Data Scarcity (CH0, XW, XZ, SL, NVC), pp. 2141–2144.
CIKMCIKM-2019-IslamLL00 #random #semantics
A Semantics Aware Random Forest for Text Classification (MZI, JL, JL, LL0, WK0), pp. 1061–1070.
CIKMCIKM-2019-KhabiriGVPM #industrial #word
Industry Specific Word Embedding and its Application in Log Classification (EK, WMG, BV, DP, PM), pp. 2713–2721.
CIKMCIKM-2019-KimRG #ambiguity #hybrid
Hybrid Deep Pairwise Classification for Author Name Disambiguation (KK, SR, CLG), pp. 2369–2372.
CIKMCIKM-2019-LiQWZCZn #visual notation
Domain Knowledge Guided Deep Atrial Fibrillation Classification and Its Visual Interpretation (XL, BQ, JW, XZ, SC, QZ), pp. 129–138.
CIKMCIKM-2019-LiuLLZS #identification
Sexual Harassment Story Classification and Key Information Identification (YL, QL, XL, QZ, LS), pp. 2385–2388.
CIKMCIKM-2019-RizosHS #learning
Augment to Prevent: Short-Text Data Augmentation in Deep Learning for Hate-Speech Classification (GR, KH, BWS), pp. 991–1000.
CIKMCIKM-2019-ShahVLFLTJS #image #multimodal
Inferring Context from Pixels for Multimodal Image Classification (MS, KV, CTL, AF, ZL, AT, CJ, CS), pp. 189–198.
CIKMCIKM-2019-ShiRWR #multi #online #sentiment
Document-Level Multi-Aspect Sentiment Classification for Online Reviews of Medical Experts (TS, VR, SW, CKR), pp. 2723–2731.
CIKMCIKM-2019-WuH19a
Enriching Pre-trained Language Model with Entity Information for Relation Classification (SW, YH), pp. 2361–2364.
CIKMCIKM-2019-WuWLH0 #sentiment
Sentiment Lexicon Enhanced Neural Sentiment Classification (CW, FW, JL, YH, XX0), pp. 1091–1100.
CIKMCIKM-2019-YanLWLWZG #image #multi #random #using
Imbalance Rectification in Deep Logistic Regression for Multi-Label Image Classification Using Random Noise Samples (WY, RL, JW, YL, JW, PZ, XG), pp. 1131–1140.
CIKMCIKM-2019-YuanLZW
Locally Slope-based Dynamic Time Warping for Time Series Classification (JY, QL, WZ, ZW), pp. 1713–1722.
CIKMCIKM-2019-ZhaoCXLZ0 #graph
Hashing Graph Convolution for Node Classification (WZ, ZC, CX, CL, TZ0, JY0), pp. 519–528.
ECIRECIR-p2-2019-PenhaCCGS #automation #documentation #performance #predict
Document Performance Prediction for Automatic Text Classification (GP, RRC, SDC, MAG, RLTS), pp. 132–139.
ICMLICML-2019-BasuGLS #streaming
Pareto Optimal Streaming Unsupervised Classification (SB0, SG, BL, SS), pp. 505–514.
ICMLICML-2019-BeygelzimerPSTW #algorithm #linear #multi #performance
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case (AB, DP, BS, DT, CYW, CZ), pp. 624–633.
ICMLICML-2019-CotterGJSSWWY #constraints #metric
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints (AC, MRG, HJ, NS, KS, SW, BEW, SY), pp. 1397–1405.
ICMLICML-2019-GuralM #embedded
Memory-Optimal Direct Convolutions for Maximizing Classification Accuracy in Embedded Applications (AG, BM), pp. 2515–2524.
ICMLICML-2019-HsiehNS
Classification from Positive, Unlabeled and Biased Negative Data (YGH, GN, MS), pp. 2820–2829.
ICMLICML-2019-HuangV
Stable and Fair Classification (LH, NKV), pp. 2879–2890.
ICMLICML-2019-HwangJY #generative #named
HexaGAN: Generative Adversarial Nets for Real World Classification (UH, DJ, SY), pp. 2921–2930.
ICMLICML-2019-LeeYLLLS #generative #robust
Robust Inference via Generative Classifiers for Handling Noisy Labels (KL, SY, KL, HL, BL, JS), pp. 3763–3772.
ICMLICML-2019-LiBS #generative #question #robust
Are Generative Classifiers More Robust to Adversarial Attacks? (YL, JB, YS), pp. 3804–3814.
ICMLICML-2019-LiCW #algorithm #kernel #linear #quantum #sublinear
Sublinear quantum algorithms for training linear and kernel-based classifiers (TL, SC, XW), pp. 3815–3824.
ICMLICML-2019-LiuLWJ #adaptation #approach
Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers (HL, ML, JW0, MIJ), pp. 4013–4022.
ICMLICML-2019-MeyerH #kernel #performance #statistics
Optimality Implies Kernel Sum Classifiers are Statistically Efficient (RAM, JH), pp. 4566–4574.
ICMLICML-2019-NamKMPSF #learning #multi #permutation
Learning Context-dependent Label Permutations for Multi-label Classification (JN, YBK, ELM, SP, RS, JF), pp. 4733–4742.
ICMLICML-2019-PolianskiiP #approach #bound #geometry #integration #monte carlo
Voronoi Boundary Classification: A High-Dimensional Geometric Approach via Weighted Monte Carlo Integration (VP, FTP), pp. 5162–5170.
ICMLICML-2019-RechtRSS #question
Do ImageNet Classifiers Generalize to ImageNet? (BR, RR, LS, VS), pp. 5389–5400.
ICMLICML-2019-ReeveK #performance #robust #symmetry
Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise (HWJR, AK), pp. 5401–5409.
ICMLICML-2019-RieckBB #graph #persistent
A Persistent Weisfeiler-Lehman Procedure for Graph Classification (BR, CB, KMB), pp. 5448–5458.
ICMLICML-2019-SatoILT #adaptation #co-evolution
Breaking Inter-Layer Co-Adaptation by Classifier Anonymization (IS, KI, GL, MT), pp. 5619–5627.
ICMLICML-2019-UstunLP
Fairness without Harm: Decoupled Classifiers with Preference Guarantees (BU, YL0, DCP), pp. 6373–6382.
ICMLICML-2019-WhitehillR #automation
Automatic Classifiers as Scientific Instruments: One Step Further Away from Ground-Truth (JW, AR), pp. 6757–6765.
ICMLICML-2019-ZhuWS #learning
Learning Classifiers for Target Domain with Limited or No Labels (PZ, HW, VS), pp. 7643–7653.
KDDKDD-2019-HartvigsenSKR #adaptation #network #policy
Adaptive-Halting Policy Network for Early Classification (TH, CS, XK, EAR), pp. 101–110.
KDDKDD-2019-Lin #multi #roadmap
Advances in Cost-sensitive Multiclass and Multilabel Classification (HTL), pp. 3187–3188.
KDDKDD-2019-LiST #higher-order #markov #multi #network #predict #random
Multi-task Recurrent Neural Networks and Higher-order Markov Random Fields for Stock Price Movement Prediction: Multi-task RNN and Higer-order MRFs for Stock Price Classification (CL, DS, DT), pp. 1141–1151.
KDDKDD-2019-RashedGS #multi
Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings (AR, JG, LST), pp. 1132–1140.
KDDKDD-2019-TangBMLLK #e-commerce #image #named #scalability
MSURU: Large Scale E-commerce Image Classification with Weakly Supervised Search Data (YT, FB, SM, YL, YL, SK), pp. 2518–2526.
KDDKDD-2019-WuHX #graph #named #network
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification (JW, JH, JX), pp. 406–415.
KDDKDD-2019-YanZDSSK #named #network
GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data (YY, JZ, MD, ES, CSS, DK), pp. 772–782.
MoDELSMoDELS-2019-NguyenRRPI #approach #automation #machine learning #metamodelling #repository
Automated Classification of Metamodel Repositories: A Machine Learning Approach (PTN, JDR, DDR, AP, LI), pp. 272–282.
ICSE-2019-AbadGZF
Supporting analysts by dynamic extraction and classification of requirements-related knowledge (ZSHA, VG, DZ, BHF), pp. 442–453.
ICSE-2019-MolinaDPRAF #data type #invariant
Training binary classifiers as data structure invariants (FM, RD, PP, GR, NA, MFF), pp. 759–770.
ICSE-2019-XiaoWCWG #android #automation #identification #named #user interface
IconIntent: automatic identification of sensitive UI widgets based on icon classification for Android apps (XX, XW, ZC, HW, PG), pp. 257–268.
SLESLE-2019-WeidmannOR #graph grammar
A feature-based classification of triple graph grammar variants (NW, RO, PR), pp. 1–14.
ASPLOSASPLOS-2019-TzimpragosMVSS #energy
Boosted Race Trees for Low Energy Classification (GT, AM, DV, DBS, TS), pp. 215–228.
CASECASE-2019-KarimDHCS #framework
A Framework for Accurate Time Series Classification Based on Partial Observation (FK, HD, SH, SC, AS), pp. 634–639.
CASECASE-2019-YangLYK #learning #realtime
Investigation of Deep Learning for Real-Time Melt Pool Classification in Additive Manufacturing (ZY, YL, HY, SK), pp. 640–647.
CASECASE-2019-ZhangLGWL #algorithm #learning #taxonomy
A Shapelet Dictionary Learning Algorithm for Time Series Classification (JZ, XL, LG0, LW, GL), pp. 299–304.
ICPCICPC-2018-HartelAL #api #clustering
Classification of APIs by hierarchical clustering (JH, HA, RL), pp. 233–243.
ICSMEICSME-2018-LeClairEM #adaptation #categorisation
Adapting Neural Text Classification for Improved Software Categorization (AL, ZE, CM), pp. 461–472.
ICSMEICSME-2018-MillsEH #automation #machine learning #maintenance #traceability
Automatic Traceability Maintenance via Machine Learning Classification (CM, JEA, SH), pp. 369–380.
ICSMEICSME-2018-SabettaB #approach #automation #commit
A Practical Approach to the Automatic Classification of Security-Relevant Commits (AS, MB), pp. 579–582.
MSRMSR-2018-MaFCAZM08 #automation #open source
Automatic classification of software artifacts in open-source applications (YM, SF, MC, VA, WZ, MM), pp. 414–425.
SCAMSCAM-2018-AlreshedyDGSG #automation
[Engineering Paper] SCC: Automatic Classification of Code Snippets (KA, DD, DMG, VS0, TAG), pp. 203–208.
CIKMCIKM-2018-BuyukcakirBC #multi #novel #online
A Novel Online Stacked Ensemble for Multi-Label Stream Classification (AB, HRB, FC), pp. 1063–1072.
CIKMCIKM-2018-DeutchF #constraints #named
CEC: Constraints based Explanation for Classifications (DD, NF), pp. 1879–1882.
CIKMCIKM-2018-GaurKASDTP #exclamation #health #quote
“Let Me Tell You About Your Mental Health!”: Contextualized Classification of Reddit Posts to DSM-5 for Web-based Intervention (MG, UK, AA, APS, RD, KT, JP), pp. 753–762.
CIKMCIKM-2018-LiLCOL #approach #documentation #modelling #topic
Dataless Text Classification: A Topic Modeling Approach with Document Manifold (XL, CL, JC, JO, CL), pp. 973–982.
CIKMCIKM-2018-MengSZ0
Weakly-Supervised Neural Text Classification (YM, JS, CZ0, JH0), pp. 983–992.
CIKMCIKM-2018-TiwariM #framework #towards
Towards a Quantum-Inspired Framework for Binary Classification (PT, MM), pp. 1815–1818.
CIKMCIKM-2018-WangM #multi #sentiment
Multi-Emotion Category Improving Embedding for Sentiment Classification (SW, XM0), pp. 1719–1722.
CIKMCIKM-2018-WangXWCC #named
DualBoost: Handling Missing Values with Feature Weights and Weak Classifiers that Abstain (WW, JX0, YW0, CC, FC0), pp. 1543–1546.
CIKMCIKM-2018-WuWL #learning #multi #sentiment
Imbalanced Sentiment Classification with Multi-Task Learning (FW, CW, JL), pp. 1631–1634.
CIKMCIKM-2018-WuZA #graph #learning
A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification (XW, LZ, LA), pp. 87–96.
CIKMCIKM-2018-ZhuangJYL #coordination #manycore #parallel
Naive Parallelization of Coordinate Descent Methods and an Application on Multi-core L1-regularized Classification (YZ, YCJ, GXY, CJL), pp. 1103–1112.
ECIRECIR-2018-Jalan0V #learning #using
Medical Forum Question Classification Using Deep Learning (RSJ, MG0, VV), pp. 45–58.
ECIRECIR-2018-SuFMMO #multi #on the #twitter
On Refining Twitter Lists as Ground Truth Data for Multi-community User Classification (TS, AF, RM, CM, IO), pp. 765–772.
ICMLICML-2018-AgarwalBD0W #approach #reduction
A Reductions Approach to Fair Classification (AA, AB, MD, JL0, HMW), pp. 60–69.
ICMLICML-2018-BaoNS #similarity
Classification from Pairwise Similarity and Unlabeled Data (HB, GN, MS), pp. 461–470.
ICMLICML-2018-HanHZ #estimation #multi #problem #scalability
Candidates vs. Noises Estimation for Large Multi-Class Classification Problem (LH, YH, TZ), pp. 1885–1894.
ICMLICML-2018-HuNSS #learning #question #robust
Does Distributionally Robust Supervised Learning Give Robust Classifiers? (WH, GN, IS, MS), pp. 2034–2042.
ICMLICML-2018-KennamerKIS #learning #named
ContextNet: Deep learning for Star Galaxy Classification (NK, DK, ATI, FJSL), pp. 2587–2595.
ICMLICML-2018-LiangSLS #comprehension #network
Understanding the Loss Surface of Neural Networks for Binary Classification (SL, RS, YL, RS), pp. 2840–2849.
ICMLICML-2018-RuffGDSVBMK
Deep One-Class Classification (LR, NG, LD, SAS, RAV, AB, EM, MK), pp. 4390–4399.
ICMLICML-2018-SanturkarSM
A Classification-Based Study of Covariate Shift in GAN Distributions (SS, LS, AM), pp. 4487–4496.
ICMLICML-2018-WehrmannCB #multi #network
Hierarchical Multi-Label Classification Networks (JW, RC, RCB), pp. 5225–5234.
ICMLICML-2018-YanKZR #metric
Binary Classification with Karmic, Threshold-Quasi-Concave Metrics (BY, OK, KZ, PR), pp. 5527–5536.
ICPRICPR-2018-AfonsoPSP #learning #using
Improving Optimum- Path Forest Classification Using Unsupervised Manifold Learning (LCSA, DCGP, ANdS, JPP), pp. 560–565.
ICPRICPR-2018-ChenDHLH #automation #clustering #image #performance
Improving Image Classification Performance with Automatically Hierarchical Label Clustering (ZC, CD, LH, DL, HH), pp. 1863–1868.
ICPRICPR-2018-ChenWWK #approximate #image #kernel #set
Riemannian kernel based Nyström method for approximate infinite-dimensional covariance descriptors with application to image set classification (KXC, XJW, RW, JK), pp. 651–656.
ICPRICPR-2018-ChenYY #image #network
Semi-supervised convolutional neural networks with label propagation for image classification (LC, SY, MY0), pp. 1319–1324.
ICPRICPR-2018-ChooSJC #multi #network
Multi-scale Recurrent Encoder-Decoder Network for Dense Temporal Classification (SKC, WS, DjJ, NIC), pp. 103–108.
ICPRICPR-2018-CuiLZLXGJZ #network
Classification Guided Deep Convolutional Network for Compressed Sensing (WC, SL, SZ, YL0, HX, XG, FJ0, DZ), pp. 2905–2910.
ICPRICPR-2018-DasRBP #documentation #image #learning #network
Document Image Classification with Intra-Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks (AD, SR, UB, SKP), pp. 3180–3185.
ICPRICPR-2018-DuanMKY #image #using
A New Single Image Super-resolution Method Using SIMK-based Classification and ISRM Technique (PD, AM, XK, CY), pp. 3043–3048.
ICPRICPR-2018-ElmogyZEE #3d #automation #framework #network
An Automated Classification Framework for Pressure Ulcer Tissues Based on 3D Convolutional Neural Network (ME, BGZ, ASE, AEB), pp. 2356–2361.
ICPRICPR-2018-FonalZW #algorithm #composition
Feature-Fusion HALS-based Algorithm for Linked CP Decomposition Model in Application to Joint EMG/MMG Signal Classification (KF, RZ, AW), pp. 928–933.
ICPRICPR-2018-GaoSXL #image #kernel #linear #set
Kernel Dual Linear Regression for Face Image Set Classification (XG, QS, HX, YL), pp. 1542–1547.
ICPRICPR-2018-GarciaLSH #complexity #metric #recommendation #using
Classifier Recommendation Using Data Complexity Measures (LPFG, ACL, MCPdS, TKH), pp. 874–879.
ICPRICPR-2018-GuoHSY #multi #rank
Low Rank Multi-Label Classification with Missing Labels (BG, CH, JS, DY), pp. 417–422.
ICPRICPR-2018-HanZG #composition #multi #network
Multi-Frequency Decomposition with Fully Convolutional Neural Network for Time Series Classification (YH, SZ, ZG), pp. 284–289.
ICPRICPR-2018-HouMZ #algorithm
A Voting-Near-Extreme-Learning-Machine Classification Algorithm (HRH, QHM, XNZ), pp. 237–241.
ICPRICPR-2018-JiangL #collaboration #representation
Discriminative Collaborative Representation and Its Application to Audio Signal Classification (YJ, FHFL), pp. 31–36.
ICPRICPR-2018-JiaXD #image
Extended Morphological Profile-based Gabor Wavelets for Hyperspectral Image Classification (SJ, HX, XD), pp. 782–787.
ICPRICPR-2018-JiaZXZH #feature model
Superpixel-Based Feature Extraction and Fusion Method for Hyperspectral and LiDAR Classification (SJ, MZ, JX, JZ, QH), pp. 764–769.
ICPRICPR-2018-KangLS #image
Object Classification of Remote Sensing Images Based on Partial Randomness Supervised Discrete Hashing (TK, YL, QSS), pp. 1935–1940.
ICPRICPR-2018-KurzendorferBSB #analysis #random #segmentation #using
Myocardial Scar Segmentation in LGE-MRI using Fractal Analysis and Random Forest Classification (TK, KB, SS, AB, CF, AKM), pp. 3168–3173.
ICPRICPR-2018-LeiZH0HL #learning #multi #rank
Multi-classification of Parkinson's Disease via Sparse Low-Rank Learning (HL, YZ, ZH, FZ0, LH, BL), pp. 3268–3272.
ICPRICPR-2018-LiangYLH #using
A Segmented Local Offset Method for Imbalanced Data Classification Using Quasi-Linear Support Vector Machine (PL, XY, WL, JH), pp. 746–751.
ICPRICPR-2018-LiCY #feature model #generative #image
Generative Band Feature Enhancement for Hyperspectral Image Classification (JL, FC, DY), pp. 1918–1923.
ICPRICPR-2018-LingLZG #image #learning #network
Semi-Supervised Learning via Convolutional Neural Network for Hyperspectral Image Classification (ZL, XL, WZ, SG), pp. 1–6.
ICPRICPR-2018-LiuDJQ #image #network #visual notation
Visual Tree Convolutional Neural Network in Image Classification (YL, YD, RJ, PQ), pp. 758–763.
ICPRICPR-2018-LiuDWZWZ #education #image #learning
Teaching Squeeze-and-Excitation PyramidNet for Imbalanced Image Classification with GAN-based Curriculum Learning (JL, AD, CW0, HZ, NW0, BZ), pp. 2444–2449.
ICPRICPR-2018-LiuF #sentiment
Introduce More Characteristics of Samples into Cross-domain Sentiment Classification (WL, XF), pp. 25–30.
ICPRICPR-2018-LiuHH #network
Lifting Scheme Based Deep Network Model for Remote Sensing Imagery Classification (XL, BH, CH), pp. 688–693.
ICPRICPR-2018-LiuLKDYZYJY #collaboration #framework #optimisation #representation
A joint optimization framework of low-dimensional projection and collaborative representation for discriminative classification (XL0, ZL, LK, ZD, JY, YZ, CY0, PJ, JY), pp. 1493–1498.
ICPRICPR-2018-LiuZKDYWLJY #image
Data Augmentation via Latent Space Interpolation for Image Classification (XL0, YZ, LK, ZD, JY, JW, SL, PJ, JY), pp. 728–733.
ICPRICPR-2018-LuYY #image
Getting Rid of Night: Thermal Image Classification Based on Feature Fusion (GL, HY, CY), pp. 2827–2832.
ICPRICPR-2018-LyuYCZZ #detection #learning
Learning Fixation Point Strategy for Object Detection and Classification (JL0, ZY, DC, YZ, HZ), pp. 2081–2086.
ICPRICPR-2018-MaO0TL
EMD-Based Entropy Features for micro-Doppler Mini-UAV Classification (XM, BSO, LS0, KAT, ZL), pp. 1295–1300.
ICPRICPR-2018-MuhammadWCA #architecture #image
Pre-trained VGGNet Architecture for Remote-Sensing Image Scene Classification (UM, WW, SPC, SA), pp. 1622–1627.
ICPRICPR-2018-MutasimBTIA #video
Effect of Artefact Removal Techniques on EEG Signals for Video Category Classification (AKM, MRB, RST, MKI, MAA), pp. 3513–3518.
ICPRICPR-2018-NieLQZJ #algorithm #incremental #learning #multi
An Incremental Multi-view Active Learning Algorithm for PolSAR Data Classification (XN, YL, HQ, BZ0, ZPJ), pp. 2251–2255.
ICPRICPR-2018-PramerdorferKL #3d #bound #multi #network
Multi-View Classification and 3D Bounding Box Regression Networks (CP, MK, MVL), pp. 734–739.
ICPRICPR-2018-RedaGSEEAEEKE #novel #precise
A Novel ADCs-Based CNN Classification System for Precise Diagnosis of Prostate Cancer (IR, MG, AS0, ME, AAEF, BOA, MAEG, AE, RK, AEB), pp. 3923–3928.
ICPRICPR-2018-RosenfeldU #concept
Action Classification via Concepts and Attributes (AR, SU), pp. 1499–1505.
ICPRICPR-2018-RoyBM #visual notation
Discriminative Latent Visual Space For Zero-Shot Object Classification (AR, BB, VM), pp. 2552–2557.
ICPRICPR-2018-SongLXG #encoding #multi #robust
Multi-Scale Cross-Band Encoding of Sectored Local Binary Pattern for Robust Texture Classification (TS, LL, LX, CG), pp. 1163–1168.
ICPRICPR-2018-SongXLG #invariant
Completed Grayscale-Inversion and Rotation Invariant Local Binary Pattern for Texture Classification (TS, LX, LL, CG), pp. 2642–2647.
ICPRICPR-2018-SuHK #analysis #component #multi #performance #using
Efficient Text Classification Using Tree-structured Multi-linear Principal Component Analysis (YS, YH, CCJK), pp. 585–590.
ICPRICPR-2018-SunLHW #algorithm #array #multi
A New ECOC Algorithm for Multiclass Microarray Data Classification (MS, KL, QH, BW), pp. 454–458.
ICPRICPR-2018-TayanovKS #learning #predict #using
Prediction-based classification using learning on Riemannian manifolds (VT, AK, CYS), pp. 591–596.
ICPRICPR-2018-TheagarajanGB #automation #generative #named
DeephESC: An Automated System for Generating and Classification of Human Embryonic Stem Cells (RT, BXG, BB), pp. 3826–3831.
ICPRICPR-2018-TuggenerESPS #dataset #detection #segmentation
DeepScores-A Dataset for Segmentation, Detection and Classification of Tiny Objects (LT, IE, JS, MP, TS), pp. 3704–3709.
ICPRICPR-2018-WangWCK #image #learning #metric #multi #set
Multiple Manifolds Metric Learning with Application to Image Set Classification (RW, XJW, KXC, JK), pp. 627–632.
ICPRICPR-2018-WangYGC #feature model
Feature Selection Ensemble for Symbolic Data Classification with AHP (MW, XY, CG, YC), pp. 868–873.
ICPRICPR-2018-WangYHYP #image
Enhancing Pix2Pix for Remote Sensing Image Classification (XW, HY, CH, JY, CP), pp. 2332–2336.
ICPRICPR-2018-WangZTL #representation #robust
Cauchy Matching Pursuit for Robust Sparse Representation and Classification (YW, CZ, YYT, LL), pp. 694–698.
ICPRICPR-2018-WeiCYLL #black box #image #using
Explain Black-box Image Classifications Using Superpixel-based Interpretation (YW, MCC, YY, SNL, SL), pp. 1640–1645.
ICPRICPR-2018-Windeatt #analysis #optimisation #using
Optimising Ensemble of Two-Class classifiers using Spectral Analysis (TW), pp. 710–715.
ICPRICPR-2018-WitmerB #image #learning #multi #using
Multi-label Classification of Stem Cell Microscopy Images Using Deep Learning (AW, BB), pp. 1408–1413.
ICPRICPR-2018-WuSZZSLPB #fourier #image
Fourier Transform based Features for Clean and Polluted Water Image Classification (XW, PS, LZ, HZ, JS, TL, UP0, MB), pp. 1707–1712.
ICPRICPR-2018-XieHLHYL #network
Deeply Supervised Residual Network for HEp-2 Cell Classification (HX, YH, HL, TH, ZY, BL), pp. 699–703.
ICPRICPR-2018-Yan0R #framework #performance #representation #scalability
An Efficient Deep Representation Based Framework for Large-Scale Terrain Classification (YY, AR0, SR), pp. 940–945.
ICPRICPR-2018-YangZWQ #analysis #detection #image #quality #recognition
Quality Classified Image Analysis with Application to Face Detection and Recognition (FY, QZ0, MW, GQ), pp. 2863–2868.
ICPRICPR-2018-Ye0 #image #invariant #learning
Rotational Invariant Discriminant Subspace Learning For Image Classification (QY, ZZ0), pp. 1217–1222.
ICPRICPR-2018-YeDW #graph
Graph-based Semi-supervised Classification with CRF and RNN (ZY, YD, FW), pp. 403–408.
ICPRICPR-2018-ZhangLYGGZ #fine-grained
Fine-Grained Age Group Classification in the wild (KZ0, NL, XY, XG, CG, ZZ), pp. 788–793.
ICPRICPR-2018-ZhangLZXSL #network
Spatial Pyramid Dilated Network for Pulmonary Nodule Malignancy Classification (GZ, YL, DZ, YX, YS, JL), pp. 3911–3916.
ICPRICPR-2018-ZhangMWZ0 #scalability #semantics #video
From Text to Video: Exploiting Mid-Level Semantics for Large-Scale Video Classification (JZ0, KM, XW0, YZ0, JF0), pp. 1695–1700.
ICPRICPR-2018-ZhangZDW #image #network
Image Exploration Procedure Classification with Spike-timing Neural Network for the Blind (TZ, TZ, BSD, JPW), pp. 3256–3261.
ICPRICPR-2018-ZhangZW #lightweight #named #network
LD-CNN: A Lightweight Dilated Convolutional Neural Network for Environmental Sound Classification (XZ, YZ, WW), pp. 373–378.
ICPRICPR-2018-ZhaoMS #image #named #network
Retraining: A Simple Way to Improve the Ensemble Accuracy of Deep Neural Networks for Image Classification (KZ, TM, ES), pp. 860–867.
ICPRICPR-2018-ZhengZ #approach #network
Accelerating the Classification of Very Deep Convolutional Network by A Cascading Approach (WZ, ZZ), pp. 355–360.
ICPRICPR-2018-Zhuang0CW #learning #multi
Multi-task Learning of Cascaded CNN for Facial Attribute Classification (NZ, YY0, SC, HW), pp. 2069–2074.
ICPRICPR-2018-ZhuDR #feature model #flexibility #image
Flexible and Discriminative Non-linear Embedding with Feature Selection for Image Classification (RZ, FD, YR), pp. 3192–3197.
KDDKDD-2018-LeeRK #graph #using
Graph Classification using Structural Attention (JBL, RAR, XK), pp. 1666–1674.
KDDKDD-2018-LiY #learning #network #policy
Learning Adversarial Networks for Semi-Supervised Text Classification via Policy Gradient (YL, JY), pp. 1715–1723.
KDDKDD-2018-Sirosh
Planet-Scale Land Cover Classification with FPGAs (JS), p. 2877.
KDDKDD-2018-YangWZL0 #multi #network
Complex Object Classification: A Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport (YY, YFW, DCZ, ZBL, YJ0), pp. 2594–2603.
KDDKDD-2018-ZhaoAS0 #dependence #performance #predict #using
Prediction-time Efficient Classification Using Feature Computational Dependencies (LZ0, AAF, MS, KZ0), pp. 2787–2796.
ICMTICMT-2018-BruelCGJKLMSV #comparison #metamodelling #model transformation #reuse
Model Transformation Reuse Across Metamodels — A Classification and Comparison of Approaches (JMB, BC, EG, JMJ, JK, JdL, GM, ES, HV), pp. 92–109.
ICSE-2018-RuscioFMM #collaboration #framework #modelling #re-engineering #research
Collaborative model-driven software engineering: a classification framework and a research map (DDR, MF, HM, IM), p. 535.
CASECASE-2018-NeumannNKM #learning
Material Classification through Knocking and Grasping by Learning of Structure-Borne Sound under Changing Acoustic Conditions (MN, KN, IK, ZCM), pp. 1269–1275.
CASECASE-2018-SussDA #approach #automation #component
An approach to automatically assign mechatronic components to an existing or identified classification (SS, CD, FA), pp. 1525–1529.
ICSTICST-2018-FengJ0F #empirical #multi #problem
An Empirical Study on Software Failure Classification with Multi-label and Problem-Transformation Techniques (YF0, JAJ, ZC0, CF), pp. 320–330.
EDMEDM-2017-GautamSSRG #modelling
Modeling Classifiers for Virtual Internships Without Participant Data (DG, ZS, DWS, VR, ACG).
EDMEDM-2017-KlinglerWKSG #performance #student
Efficient Feature Embeddings for Student Classification with Variational Auto-encoders (SK, RW, TK, BS, MHG).
EDMEDM-2017-RomeroEGGM #automation #learning #towards
Towards Automatic Classification of Learning Objects: Reducing the Number of Used Features (CR, PGE, EG, AZG, VHM).
ICSMEICSME-2017-TerdchanakulHPM #debugging #n-gram #using
Bug or Not? Bug Report Classification Using N-Gram IDF (PT, HH, PP, KM), pp. 534–538.
MSRMSR-2017-GhotraMH #fault #feature model #modelling #scalability
A large-scale study of the impact of feature selection techniques on defect classification models (BG, SM, AEH), pp. 146–157.
MSRMSR-2017-NiL #effectiveness #predict #using
Cost-effective build outcome prediction using cascaded classifiers (AN, ML0), pp. 455–458.
MSRMSR-2017-Patil #concept #fault
Concept-based classification of software defect reports (SP), pp. 182–186.
MSRMSR-2017-RajbahadurWKH #fault #modelling #using
The impact of using regression models to build defect classifiers (GKR, SW0, YK, AEH), pp. 135–145.
CoGCIG-2017-GoudelisTKK #3d #effectiveness #feature model
3D cylindrical trace transform based feature extraction for effective human action classification (GG, GT, KK, SDK), pp. 96–103.
CIKMCIKM-2017-ChengZZKZW #network #sentiment
Aspect-level Sentiment Classification with HEAT (HiErarchical ATtention) Network (JC, SZ, JZ, IK, XZ0, HW0), pp. 97–106.
CIKMCIKM-2017-DangCWZC #kernel #learning
Unsupervised Matrix-valued Kernel Learning For One Class Classification (SD, XC, YW0, JZ, FC0), pp. 2031–2034.
CIKMCIKM-2017-HaqueWCDKH #multi #named #online
FUSION: An Online Method for Multistream Classification (AH, ZW, SC, BD, LK, KWH), pp. 919–928.
CIKMCIKM-2017-HuangYLP #adaptation
Length Adaptive Recurrent Model for Text Classification (ZH, ZY, SL, RP), pp. 1019–1027.
CIKMCIKM-2017-HuPJL #graph #network
Graph Ladder Networks for Network Classification (RH, SP, JJ0, GL), pp. 2103–2106.
CIKMCIKM-2017-PatwariGB #detection #multi #named
TATHYA: A Multi-Classifier System for Detecting Check-Worthy Statements in Political Debates (AP, DG, SB), pp. 2259–2262.
CIKMCIKM-2017-SchaferL #performance
Fast and Accurate Time Series Classification with WEASEL (PS0, UL), pp. 637–646.
CIKMCIKM-2017-SuzannaA
Hierarchical Module Classification in Mixed-initiative Conversational Agent System (SXYS, ALL), pp. 2535–2538.
CIKMCIKM-2017-VeysehEDL
A Temporal Attentional Model for Rumor Stance Classification (APBV, JE, DD, DL), pp. 2335–2338.
CIKMCIKM-2017-XuWXQ #graph #network #recursion
Attentive Graph-based Recursive Neural Network for Collective Vertex Classification (QX, QW, CX, LQ), pp. 2403–2406.
CIKMCIKM-2017-YeHHCLQS #using
Nationality Classification Using Name Embeddings (JY, SH, YH, BC, ML, HQ, SS), pp. 1897–1906.
CIKMCIKM-2017-ZhuRXLYW #clustering #pattern matching #social
Cluster-level Emotion Pattern Matching for Cross-Domain Social Emotion Classification (EZ, YR, HX0, YL, JY0, FLW), pp. 2435–2438.
ECIRECIR-2017-BaruaP #query #using
Named Entity Classification Using Search Engine's Query Suggestions (JB, DP), pp. 612–618.
ECIRECIR-2017-McDonaldMO #semantics #using #word
Enhancing Sensitivity Classification with Semantic Features Using Word Embeddings (GM, CM, IO), pp. 450–463.
ECIRECIR-2017-ValavanisSK #image #modelling
Fusion of Bag-of-Words Models for Image Classification in the Medical Domain (LV, SS, TK), pp. 134–145.
ICMLICML-2017-BeckhamP #probability
Unimodal Probability Distributions for Deep Ordinal Classification (CB, CJP), pp. 411–419.
ICMLICML-2017-DembczynskiKKN #analysis #consistency #revisited
Consistency Analysis for Binary Classification Revisited (KD, WK, OK, NN), pp. 961–969.
ICMLICML-2017-FutomaHH #detection #learning #multi #process
Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier (JF, SH, KAH), pp. 1174–1182.
ICMLICML-2017-JerniteCS #estimation #learning
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation (YJ, AC, DAS), pp. 1665–1674.
ICMLICML-2017-KrishnamurthyAH #learning
Active Learning for Cost-Sensitive Classification (AK, AA, TKH, HDI, JL0), pp. 1915–1924.
ICMLICML-2017-OdenaOS #image #synthesis
Conditional Image Synthesis with Auxiliary Classifier GANs (AO, CO, JS), pp. 2642–2651.
ICMLICML-2017-RealMSSSTLK #evolution #image #scalability
Large-Scale Evolution of Image Classifiers (ER, SM, AS, SS, YLS, JT, QVL, AK), pp. 2902–2911.
ICMLICML-2017-SakaiPNS
Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data (TS, MCdP, GN, MS), pp. 2998–3006.
ICMLICML-2017-ThiLNT #probability #problem
Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification (HALT, HML, PDN, BT), pp. 3394–3403.
ICMLICML-2017-UbaruM #multi #testing
Multilabel Classification with Group Testing and Codes (SU, AM), pp. 3492–3501.
ICMLICML-2017-Villacampa-Calvo #multi #process #scalability #using
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation (CVC, DHL), pp. 3550–3559.
ICMLICML-2017-YangKT #network #video
Tensor-Train Recurrent Neural Networks for Video Classification (YY, DK, VT), pp. 3891–3900.
KDDKDD-2017-AndersonM #machine learning
Machine Learning for Encrypted Malware Traffic Classification: Accounting for Noisy Labels and Non-Stationarity (BA, DAM), pp. 1723–1732.
KDDKDD-2017-Tagami #approximate #multi #named #nearest neighbour
AnnexML: Approximate Nearest Neighbor Search for Extreme Multi-label Classification (YT), pp. 455–464.
KDDKDD-2017-YenHDRDX #named #parallel
PPDsparse: A Parallel Primal-Dual Sparse Method for Extreme Classification (IEHY, XH, WD0, PR, ISD, EPX), pp. 545–553.
OnwardOnward-2017-WrennK #design #error message #fault #process
Error messages are classifiers: a process to design and evaluate error messages (JW, SK), pp. 134–147.
ASEASE-2017-Mills #automation #towards #traceability
Towards the automatic classification of traceability links (CM), pp. 1018–1021.
ESEC-FSEESEC-FSE-2017-Mills #automation #traceability
Automating traceability link recovery through classification (CM), pp. 1068–1070.
GPCEGPCE-2017-LinsbauerBG
A classification of variation control systems (LL, TB, PG), pp. 49–62.
CASECASE-2017-ChenWWWC #big data #detection #fault #multi
Big data analytic for multivariate fault detection and classification in semiconductor manufacturing (YJC, BCW, JZW, YCW, CFC), pp. 731–736.
CASECASE-2017-LiXLK #approach #learning #physics
Improving colorectal polyp classification based on physical examination data - A ensemble learning approach (CL, XX, JL, NK), pp. 193–194.
CASECASE-2017-TanCT #automation #evaluation #layout #multi
Multiple binary classifiers to analyse decision of non-compliance: For automated evaluation of piping layout (WCT, IMC, HKT), pp. 80–85.
CAVCAV-2017-AdimoolamDDKJ #embedded
Classification and Coverage-Based Falsification for Embedded Control Systems (ASA, TD, AD, JK, XJ), pp. 483–503.
JCDLJCDL-2016-BornandBS #using
Routing Memento Requests Using Binary Classifiers (NJB, LB, HVdS), pp. 63–72.
EDMEDM-2016-AtapattuFT #approach #topic #visual notation
Topic-wise Classification of MOOC Discussions: A Visual Analytics Approach (TA, KF, HT), pp. 276–281.
EDMEDM-2016-BhatnagarDLC #physics #self #student
Text Classification of Student Self-Explanations in College Physics Questions (SB, MCD, NL, ESC), pp. 571–572.
EDMEDM-2016-RusBMMRY #online #tutorial
Preliminary Results On Dialogue Act and Subact Classification in Chat-based Online Tutorial Dialogues (VR, RB, NM, DMM, SR, MY), pp. 630–631.
SANERSANER-2016-DamZ #identification #natural language
Software Language Identification with Natural Language Classifiers (JKvD, VZ), pp. 624–628.
SANERSANER-2016-FontanaDWYZ #concept #smell
Antipattern and Code Smell False Positives: Preliminary Conceptualization and Classification (FAF, JD0, BW, AY, MZ), pp. 609–613.
IFM-2016-ChenAGSM #behaviour #on the #robust #verification
On Robust Malware Classifiers by Verifying Unwanted Behaviours (WC, DA0, ADG, CAS, IM), pp. 326–341.
CoGCIG-2016-ClericoCPMTFGJ #game studies #predict #video
Biometrics and classifier fusion to predict the fun-factor in video gaming (AC, CC, MP, PEM, ST, THF, JCG, PLJ), pp. 1–8.
CoGCIG-2016-DeboeverieRAVP #game studies #gesture #machine learning
Human gesture classification by brute-force machine learning for exergaming in physiotherapy (FD, SR, GA, PV, WP), pp. 1–7.
DiGRADiGRA-FDG-2016-KnauerM #game studies #visual notation
Two Worlds, One Gameplay: A Classification of Visual AR Games (MK, JM).
CIKMCIKM-2016-BonabC #data type #framework #online
A Theoretical Framework on the Ideal Number of Classifiers for Online Ensembles in Data Streams (HRB, FC), pp. 2053–2056.
CIKMCIKM-2016-ChandraHKA #adaptation #framework #multi
An Adaptive Framework for Multistream Classification (SC, AH, LK, CCA), pp. 1181–1190.
CIKMCIKM-2016-CormackG #learning #reliability #scalability
Scalability of Continuous Active Learning for Reliable High-Recall Text Classification (GVC, MRG), pp. 1039–1048.
CIKMCIKM-2016-GongC #modelling #sequence
Model-Based Oversampling for Imbalanced Sequence Classification (ZG, HC), pp. 1009–1018.
CIKMCIKM-2016-LiKZH #network #on the
On Transductive Classification in Heterogeneous Information Networks (XL, BK, YZ, ZH0), pp. 811–820.
CIKMCIKM-2016-LiLF #approach #multi
Multi-View Time Series Classification: A Discriminative Bilinear Projection Approach (SL0, YL, YF0), pp. 989–998.
CIKMCIKM-2016-LiSLNF #knowledge base #named #topic #twitter #word
TweetSift: Tweet Topic Classification Based on Entity Knowledge Base and Topic Enhanced Word Embedding (QL, SS, XL, AN, RF), pp. 2429–2432.
CIKMCIKM-2016-SoleimaniM #documentation #modelling #multi #topic
Semi-supervised Multi-Label Topic Models for Document Classification and Sentence Labeling (HS, DJM0), pp. 105–114.
CIKMCIKM-2016-WangTAL #documentation
Linked Document Embedding for Classification (SW, JT, CCA, HL0), pp. 115–124.
CIKMCIKM-2016-XuYLH
Cross-lingual Text Classification via Model Translation with Limited Dictionaries (RX, YY, HL, AH), pp. 95–104.
CIKMCIKM-2016-ZhangDH #ambiguity #case study #online #using
Bayesian Non-Exhaustive Classification A Case Study: Online Name Disambiguation using Temporal Record Streams (BZ, MD, MAH), pp. 1341–1350.
CIKMCIKM-2016-ZhangYZZ #matrix #network
Collective Classification via Discriminative Matrix Factorization on Sparsely Labeled Networks (DZ, JY, XZ, CZ), pp. 1563–1572.
CIKMCIKM-2016-ZhengC #constraints #learning #probability
Regularizing Structured Classifier with Conditional Probabilistic Constraints for Semi-supervised Learning (VWZ, KCCC), pp. 1029–1038.
ECIRECIR-2016-BalikasA #multi #using
Multi-label, Multi-class Classification Using Polylingual Embeddings (GB, MRA), pp. 723–728.
ICMLICML-2016-BaiRWS #difference #geometry #learning
Differential Geometric Regularization for Supervised Learning of Classifiers (QB, SR, ZW, SS), pp. 1879–1888.
ICMLICML-2016-FernandoG #learning #video
Learning End-to-end Video Classification with Rank-Pooling (BF, SG), pp. 1187–1196.
ICMLICML-2016-KantchelianTJ
Evasion and Hardening of Tree Ensemble Classifiers (AK, JDT, ADJ), pp. 2387–2396.
ICMLICML-2016-LiWPA #multi
Conditional Bernoulli Mixtures for Multi-label Classification (CL, BW, VP, JAA), pp. 2482–2491.
ICMLICML-2016-MartinsA #multi
From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification (AFTM, RFA), pp. 1614–1623.
ICMLICML-2016-NatarajanKRD #multi
Optimal Classification with Multivariate Losses (NN, OK, PR, ISD), pp. 1530–1538.
ICMLICML-2016-OkOSY #crowdsourcing
Optimality of Belief Propagation for Crowdsourced Classification (JO, SO, JS, YY), pp. 535–544.
ICMLICML-2016-SuhZA #complexity
The Label Complexity of Mixed-Initiative Classifier Training (JS, XZ0, SA), pp. 2800–2809.
ICMLICML-2016-YenHRZD #approach #multi
PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification (IEHY, XH, PR, KZ, ISD), pp. 3069–3077.
ICMLICML-2016-ZhangLL #image #network #scalability
Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification (YZ, KL, HL), pp. 612–621.
ICPRICPR-2016-AgarwalSV
Fingerprint sensor classification via Mélange of handcrafted features (AA0, RS0, MV), pp. 3001–3006.
ICPRICPR-2016-AmeurVC #recognition
Sub-classification strategies for tree species recognition (RBA, LV, DC), pp. 2139–2144.
ICPRICPR-2016-BaiCWJ0H #clustering #graph #kernel
Shape classification with a vertex clustering graph kernel (LB0, LC, YW0, XJ0, XB0, ERH), pp. 2634–2639.
ICPRICPR-2016-BarddalGBE #benchmark #data type #metric
A benchmark of classifiers on feature drifting data streams (JPB, HMG, AdSBJ, FE), pp. 2180–2185.
ICPRICPR-2016-BayramogluKH #image #independence #learning
Deep learning for magnification independent breast cancer histopathology image classification (NB, JK, JH), pp. 2440–2445.
ICPRICPR-2016-Brandtberg #analysis #fourier #fuzzy #multi #order #rank #using
Virtual hexagonal and multi-scale operator for fuzzy rank order texture classification using one-dimensional generalised Fourier analysis (TB), pp. 2018–2024.
ICPRICPR-2016-BSSH #approach #network #using
HEp-2 cell classification using artificial neural network approach (DB, KS, NH), pp. 84–89.
ICPRICPR-2016-CorbelliBGC #analysis #documentation #layout
Historical document digitization through layout analysis and deep content classification (AC, LB, CG, RC), pp. 4077–4082.
ICPRICPR-2016-DaoodRB #multi #recognition #using
Pollen recognition using a multi-layer hierarchical classifier (AD, ER, MB), pp. 3091–3096.
ICPRICPR-2016-DasguptaN #fine-grained #multi
Leveraging multiple tasks to regularize fine-grained classification (RD, AMN), pp. 3476–3481.
ICPRICPR-2016-DubosBAS
ROC-based cost-sensitive classification with a reject option (CD, SB, SA, RS), pp. 3320–3325.
ICPRICPR-2016-FioriMF #design #multi
An optimal multiclass classifier design (MF, MDM, AF), pp. 480–485.
ICPRICPR-2016-GonzalezVT #invariant #learning
Learning rotation invariant convolutional filters for texture classification (DM, MV, DT), pp. 2012–2017.
ICPRICPR-2016-GoswamiRSV #normalisation
Improving classifier fusion via Pool Adjacent Violators normalization (GG, NKR, RS0, MV), pp. 1011–1016.
ICPRICPR-2016-GrimmMBS #using
Sleep position classification from a depth camera using Bed Aligned Maps (TG, MM, AB, RS), pp. 319–324.
ICPRICPR-2016-HasegawaH #image #named #network #using
PLSNet: A simple network using Partial Least Squares regression for image classification (RH, KH), pp. 1601–1606.
ICPRICPR-2016-HouXX0 #graph #learning
Semi-supervised learning competence of classifiers based on graph for dynamic classifier selection (CH, YX, ZX, JS0), pp. 3650–3654.
ICPRICPR-2016-HuangYZZ #reduction #robust
Rough Neighborhood Covering Reduction for robust classification (WH, XY, CZ, NZ), pp. 3308–3313.
ICPRICPR-2016-IshiiSIMSIN #detection #multi
Detection by classification of buildings in multispectral satellite imagery (TI, ESS, SI, YM, AS, HI0, RN), pp. 3344–3349.
ICPRICPR-2016-JamesC #social #social media
Evolutionary data purification for social media classification (SJ, JPC), pp. 2676–2681.
ICPRICPR-2016-JiaSZY #network
Deep convolutional neural network based HEp-2 cell classification (XJ, LS, XZ, SY), pp. 77–80.
ICPRICPR-2016-Julca-AguilarHM
Subexpression and dominant symbol histograms for spatial relation classification in mathematical expressions (FDJA, NSTH, HM, CVG), pp. 3446–3451.
ICPRICPR-2016-KawanishiDIMF #learning #robust
Misclassification tolerable learning for robust pedestrian orientation classification (YK, DD, II, HM, HF), pp. 486–491.
ICPRICPR-2016-KhareSKCLB #metric #quality #video
A quad tree based method for blurred and non-blurred video text frames classification through quality metrics (VK, PS, AK, CSC, TL, MB), pp. 4023–4028.
ICPRICPR-2016-KimuraKSK #multi #performance #random #scalability
Fast random k-labELsets for large-scale multi-label classification (KK, MK, LS, SK), pp. 438–443.
ICPRICPR-2016-KimV #semantics #using
Deep Action Unit classification using a binned intensity loss and semantic context model (EK, SV), pp. 4136–4141.
ICPRICPR-2016-KrijtheL16a
Optimistic semi-supervised least squares classification (JHK, ML), pp. 1677–1682.
ICPRICPR-2016-LangenkamperN #architecture #detection #learning #online #realtime
COATL - a learning architecture for online real-time detection and classification assistance for environmental data (DL, TWN), pp. 597–602.
ICPRICPR-2016-LiaoLL #multi #network #robust #using
Skin disease classification versus skin lesion characterization: Achieving robust diagnosis using multi-label deep neural networks (HL, YL, JL), pp. 355–360.
ICPRICPR-2016-LiHZXZ
HEp-2 specimen classification via deep CNNs and pattern histogram (HL0, HH, WSZ, XX, JZ), pp. 2145–2149.
ICPRICPR-2016-LiSZY #network
HEp-2 specimen classification with fully convolutional network (YL, LS, XZ, SY), pp. 96–100.
ICPRICPR-2016-Liu16a #learning #multi #network #scalability
Hierarchical learning for large multi-class network classification (LL), pp. 2307–2312.
ICPRICPR-2016-LiuKWK #recognition #word
Scene text recognition with CNN classifier and WFST-based word labeling (XL, TK, XW, KK), pp. 3999–4004.
ICPRICPR-2016-NguyenVPG
An integrated descriptor for texture classification (VLN, NSV, HHP, PHG), pp. 2006–2011.
ICPRICPR-2016-NilssonO #complexity #pattern matching #pattern recognition #recognition
Estimates of Classification Complexity for Myoelectric Pattern Recognition (NN, MOC), pp. 2682–2687.
ICPRICPR-2016-NookaCVSP #adaptation #network
Adaptive hierarchical classification networks (SPN, SC, KV, SS, RWP), pp. 3578–3583.
ICPRICPR-2016-NorooziMNEA #predict #recognition
Fusion of classifier predictions for audio-visual emotion recognition (FN, MM, AN, SE, GA), pp. 61–66.
ICPRICPR-2016-Norov-ErdeneKSK #locality #multi #problem
Locality in multi-label classification problems (BNE, MK, LS, KK), pp. 2319–2324.
ICPRICPR-2016-OliveauS #image #semantics
Semantic-free attributes for image classification (QO, HS), pp. 1577–1582.
ICPRICPR-2016-PrasathKOGHSP #random #segmentation #using
HEp-2 cell classification and segmentation using motif texture patterns and spatial features with random forests (VBSP, YMK, ZAO, JBG, AH, GS, KP), pp. 90–95.
ICPRICPR-2016-PreslesD #invariant
A distance-based shape descriptor invariant to similitude and its application to shape classification (BP, JD), pp. 2598–2603.
ICPRICPR-2016-RiabchenkoMAITG #fine-grained
Learned vs. engineered features for fine-grained classification of aquatic macroinvertebrates (ER, KM, IA0, AI, VT, MG, SK), pp. 2276–2281.
ICPRICPR-2016-RoyCSC #predict
Meta-regression based pool size prediction scheme for dynamic selection of classifiers (AR, RMOC, RS, GDCC), pp. 216–221.
ICPRICPR-2016-RoyDB #documentation #image #network
Generalized stacking of layerwise-trained Deep Convolutional Neural Networks for document image classification (SR, AD, UB), pp. 1273–1278.
ICPRICPR-2016-SinoaraRR #semantics
Semantic role-based representations in text classification (RAS, RGR, SOR), pp. 2313–2318.
ICPRICPR-2016-SunKK #multi
Multi-label classification with meta-label-specific features (LS, MK, KK), pp. 1612–1617.
ICPRICPR-2016-TocaPC
AutoMarkov DNNs for object classification (CT, CP, MC), pp. 3452–3457.
ICPRICPR-2016-Troya-GalvisGB #analysis #collaboration #image #segmentation
Collaborative segmentation and classification for remote sensing image analysis (ATG, PG, LBÉ), pp. 829–834.
ICPRICPR-2016-VoTPV #detection #modelling
Model-based classification and novelty detection for point pattern data (BNV, NQT, DQP, BTV), pp. 2622–2627.
ICPRICPR-2016-WangHG #learning #novel
A novel fingerprint classification method based on deep learning (RW, CH, TG), pp. 931–936.
ICPRICPR-2016-WangTLW #representation #robust
Information-theoretic atomic representation for robust pattern classification (YW, YYT, LL, PSPW), pp. 3685–3690.
ICPRICPR-2016-WangZYP #detection
Anomaly detection in crowded scenes by SL-HOF descriptor and foreground classification (SW, EZ, JY, FP), pp. 3398–3403.
ICPRICPR-2016-Williams #network #using
Underwater target classification in synthetic aperture sonar imagery using deep convolutional neural networks (DPW), pp. 2497–2502.
ICPRICPR-2016-WimmerUH #novel
A novel filterbank especially designed for the classification of colonic polyps (GW, AU, MH), pp. 2150–2155.
ICPRICPR-2016-YeZL #documentation #network #online #random
Joint training of conditional random fields and neural networks for stroke classification in online handwritten documents (JYY, YMZ, CLL), pp. 3264–3269.
ICPRICPR-2016-YildizU #incremental #order #using
Incremental construction of rule ensembles using classifiers produced by different class orderings (OTY, AU), pp. 492–497.
ICPRICPR-2016-ZhaoSJ #identification #robust
Robust signal identification for dynamic pattern classification (RZ, GS, QJ), pp. 3910–3915.
ICPRICPR-2016-ZhongGS
A DBN-crf for spectral-spatial classification of hyperspectral data (PZ0, ZG, CBS), pp. 1219–1224.
KDDKDD-2016-ChiangLL #coordination #linear #manycore #parallel #scalability
Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments (WLC, MCL, CJL), pp. 1485–1494.
KDDKDD-2016-NandanwarM #network
Structural Neighborhood Based Classification of Nodes in a Network (SN, MNM), pp. 1085–1094.
KDDKDD-2016-Ribeiro0G #predict #quote #trust #why
“Why Should I Trust You?”: Explaining the Predictions of Any Classifier (MTR, SS0, CG), pp. 1135–1144.
ECMFAECMFA-2016-AtkinsonK #ontology
Demystifying Ontological Classification in Language Engineering (CA, TK), pp. 83–100.
ASEASE-2016-WangWCW #crowdsourcing #testing
Local-based active classification of test report to assist crowdsourced testing (JW, SW, QC, QW), pp. 190–201.
FSEFSE-2016-PanichellaSGVCG #development #named
ARdoc: app reviews development oriented classifier (SP, ADS, EG, CAV, GC, HCG), pp. 1023–1027.
ICSE-2016-FavaSOSW #crowdsourcing #game studies
Crowdsourcing program preconditions via a classification game (DF, DS, JCO, MS, EJWJ), pp. 1086–1096.
ICSE-2016-Tantithamthavorn #automation #fault #modelling #optimisation #parametricity #predict
Automated parameter optimization of classification techniques for defect prediction models (CT, SM, AEH, KM), pp. 321–332.
ICSE-2016-ZhangZZH #fault #predict #using
Cross-project defect prediction using a connectivity-based unsupervised classifier (FZ0, QZ, YZ0, AEH), pp. 309–320.
ASPLOSASPLOS-2016-MukkaraBS #named
Whirlpool: Improving Dynamic Cache Management with Static Data Classification (AM, NB, DS0), pp. 113–127.
CASECASE-2016-ChenKZW #algorithm #clustering #novel
A novel under-sampling algorithm based on Iterative-Partitioning Filters for imbalanced classification (XC, QK, MZ, ZW), pp. 490–494.
CASECASE-2016-SharabianiSD #novel #representation
A novel Bayesian and Chain Rule Model on symbolic representation for time series classification (AS, AS, HD), pp. 1014–1019.
CASECASE-2016-SussD #behaviour #component #performance #simulation
Classification of mechatronic components for efficient plant behaviour simulation (SS, CD), pp. 1146–1151.
DocEngDocEng-2015-FerreiraLCFSR #automation #documentation #summary #using
Automatic Document Classification using Summarization Strategies (RF, RDL, LdSC, FF, SJS, MR), pp. 69–72.
DocEngDocEng-2015-SvendsenA #documentation
Change Classification in Graphics-Intensive Digital Documents (JS, ABA), pp. 203–206.
HTHT-2015-BurnapCS #analysis #communication #twitter
Machine Classification and Analysis of Suicide-Related Communication on Twitter (PB, WC, JS), pp. 75–84.
EDMEDM-2015-EmondB #process #sequence #student #using
Analyzing Student Inquiry Data Using Process Discovery and Sequence Classification (BE, SB), pp. 412–415.
EDMEDM-2015-LuoK0 #performance #predict #student
Discrimination-Aware Classifiers for Student Performance Prediction (LL, IK, WL0), pp. 384–387.
EDMEDM-2015-SameiRNM #online
Hierarchical Dialogue Act Classification in Online Tutoring Sessions (BS, VR, BN, DMM), pp. 600–601.
EDMEDM-2015-StrechtCSMA #algorithm #case study #comparative #modelling #performance #student
A Comparative Study of Regression and Classification Algorithms for Modelling Students' Academic Performance (PS, LC0, CS, JMM, RA), pp. 392–395.
MSRMSR-2015-OhiraKYYMLFHIM #dataset #debugging
A Dataset of High Impact Bugs: Manually-Classified Issue Reports (MO, YK, YY, HY, YM, NL, KF, HH, AI, KiM), pp. 518–521.
CHI-PLAYCHI-PLAY-2015-HeintzL #game studies
The Game Genre Map: A Revised Game Classification (SH, ELCL), pp. 175–184.
CoGVS-Games-2015-BalducciGC #design #game studies
Classification of Affective Data to Evaluate the Level Design in a Role-Playing Videogame (FB, CG, RC), pp. 1–8.
CHICHI-2015-FaircloughKG #interactive #realtime
Classification Accuracy from the Perspective of the User: Real-Time Interaction with Physiological Computing (SHF, AJK, KMG), pp. 3029–3038.
CHICHI-2015-KayPK #evaluation #how #overview
How Good is 85%?: A Survey Tool to Connect Classifier Evaluation to Acceptability of Accuracy (MK, SNP, JAK), pp. 347–356.
CHICHI-2015-SatoYOSHTHR #interactive #named
SpecTrans: Versatile Material Classification for Interaction with Textureless, Specular and Transparent Surfaces (MS, SY, AO, BS, AH, TT, MH, RR), pp. 2191–2200.
CSCWCSCW-2015-ChengB #hybrid #machine learning #named
Flock: Hybrid Crowd-Machine Learning Classifiers (JC, MSB), pp. 600–611.
HCIHCI-IT-2015-SatoAOO #analysis #automation #image
Automatic Classification Between Involuntary and Two Types of Voluntary Blinks Based on an Image Analysis (HS, KA, SO, MO), pp. 140–149.
HCIHIMI-IKD-2015-KastratiIY #documentation #framework #using
A General Framework for Text Document Classification Using SEMCON and ACVSR (ZK, ASI, SYY), pp. 310–319.
ICEISICEIS-v1-2015-FerrandinENSA #approach
A Centroid-based Approach for Hierarchical Classification (MF, FE, JCN, EES, BCÁ), pp. 25–33.
ICEISICEIS-v1-2015-PfaffK #automation #benchmark #documentation #identification #metric #natural language
Natural Language Processing Techniques for Document Classification in IT Benchmarking — Automated Identification of Domain Specific Terms (MP, HK), pp. 360–366.
ICEISICEIS-v1-2015-SunB #mining #process
Function-based Case Classification for Improving Business Process Mining (YS, BB), pp. 251–258.
CIKMCIKM-2015-AiWSYZC #multi
Best First Over-Sampling for Multilabel Classification (XA, JW0, VSS, YY, PZ, ZC), pp. 1803–1806.
CIKMCIKM-2015-BerardiEMO0 #automation #identification
Semi-Automated Text Classification for Sensitivity Identification (GB, AE, CM, IO, FS0), pp. 1711–1714.
CIKMCIKM-2015-GuiLXLW #estimation #novel
A Novel Class Noise Estimation Method and Application in Classification (LG0, QL0, RX, ML, QW), pp. 1081–1090.
CIKMCIKM-2015-HongWW #clustering #learning
Clustering-based Active Learning on Sensor Type Classification in Buildings (DH, HW, KW), pp. 363–372.
CIKMCIKM-2015-JinZPDLH #learning #multi #semantics
Heterogeneous Multi-task Semantic Feature Learning for Classification (XJ0, FZ, SJP, CD, PL0, QH), pp. 1847–1850.
CIKMCIKM-2015-KhudaBukhshBW #case study #detection #effectiveness #query #self
Building Effective Query Classifiers: A Case Study in Self-harm Intent Detection (ARK, PNB, RWW), pp. 1735–1738.
CIKMCIKM-2015-LiZ #statistics
Associative Classification with Statistically Significant Positive and Negative Rules (JL, ORZ), pp. 633–642.
CIKMCIKM-2015-RudraGGGG #approach #microblog
Extracting Situational Information from Microblogs during Disaster Events: a Classification-Summarization Approach (KR, SG, NG, PG, SG0), pp. 583–592.
CIKMCIKM-2015-ViegasGMR #documentation #effectiveness #lazy evaluation #naive bayes #parallel #performance
Parallel Lazy Semi-Naive Bayes Strategies for Effective and Efficient Document Classification (FV, MAG, WM, LCdR), pp. 1071–1080.
CIKMCIKM-2015-WangZTCZ #graph
Defragging Subgraph Features for Graph Classification (HW, PZ0, IWT, LC0, CZ), pp. 1687–1690.
CIKMCIKM-2015-WanLKYGCH #learning #network
Classification with Active Learning and Meta-Paths in Heterogeneous Information Networks (CW, XL, BK, XY, QG, DWLC, JH0), pp. 443–452.
CIKMCIKM-2015-YangZ #framework #graph #online #optimisation
A Min-Max Optimization Framework For Online Graph Classification (PY, PZ), pp. 643–652.
ECIRECIR-2015-CanneytCD #sentiment #topic #twitter
Topic-Dependent Sentiment Classification on Twitter (SVC, NC, BD), pp. 441–446.
ECIRECIR-2015-EfremovaGC
Classification of Historical Notary Acts with Noisy Labels (JE, AMG, TC), pp. 49–54.
ECIRECIR-2015-HagenPBS #detection #sentiment #twitter #using
Twitter Sentiment Detection via Ensemble Classification Using Averaged Confidence Scores (MH, MP, MB, BS), pp. 741–754.
ECIRECIR-2015-RomeoIT #documentation #knowledge-based #multi #representation
Knowledge-Based Representation for Transductive Multilingual Document Classification (SR, DI, AT), pp. 92–103.
ECIRECIR-2015-SaracIGD #concept #flexibility #framework #named
ConceptFusion: A Flexible Scene Classification Framework (MIS, AI, EG, PD), pp. 55–60.
ECIRECIR-2015-SchindlerR #approach #music
An Audio-Visual Approach to Music Genre Classification through Affective Color Features (AS, AR), pp. 61–67.
ICMLICML-2015-GasseAE #composition #multi #on the #set
On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property (MG, AA, HE), pp. 2531–2539.
ICMLICML-2015-HazanLM #rank
Classification with Low Rank and Missing Data (EH, RL, YM), pp. 257–266.
ICMLICML-2015-HuangWSLC #image #learning #metric #set #symmetry
Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application to Image Set Classification (ZH, RW, SS, XL, XC), pp. 720–729.
ICMLICML-2015-OsadchyHK
K-hyperplane Hinge-Minimax Classifier (MO, TH, DK), pp. 1558–1566.
ICMLICML-2015-RamaswamyT0
Convex Calibrated Surrogates for Hierarchical Classification (HGR, AT, SA), pp. 1852–1860.
ICMLICML-2015-RichmanM #constraints
Dynamic Sensing: Better Classification under Acquisition Constraints (OR, SM), pp. 267–275.
KDDKDD-2015-BifetMRHP #big data #data type #evaluation #online #performance
Efficient Online Evaluation of Big Data Stream Classifiers (AB, GDFM, JR, GH, BP), pp. 59–68.
KDDKDD-2015-ChakrabortyBSPY #framework #learning #named #novel
BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification (SC, VNB, ARS, SP, JY), pp. 99–108.
KDDKDD-2015-ChuHTLL #linear #parametricity
Warm Start for Parameter Selection of Linear Classifiers (BYC, CHH, CHT, CYL, CJL), pp. 149–158.
KDDKDD-2015-OkumuraST #analysis #incremental #linear #problem
Quick Sensitivity Analysis for Incremental Data Modification and Its Application to Leave-one-out CV in Linear Classification Problems (SO, YS, IT), pp. 885–894.
KDDKDD-2015-RoyTZLHNM
Dynamic Hierarchical Classification for Patient Risk-of-Readmission (SBR, AT, KZ, RL, DH, SN, AM), pp. 1691–1700.
KDDKDD-2015-SethiYRVR #machine learning #scalability #using
Scalable Machine Learning Approaches for Neighborhood Classification Using Very High Resolution Remote Sensing Imagery (MS, YY, AR, RRV, SR), pp. 2069–2078.
KDDKDD-2015-SunAYMMBY #learning
Transfer Learning for Bilingual Content Classification (QS, MSA, BY, CM, VM, AB, JY), pp. 2147–2156.
MLDMMLDM-2015-Babu #identification #using
Offline Writer Identification in Tamil Using Bagged Classification Trees (SB), pp. 342–354.
MLDMMLDM-2015-DavidsenSP #fuzzy #search-based
Local and Global Genetic Fuzzy Pattern Classifiers (SAD, ES, MP), pp. 55–69.
MLDMMLDM-2015-Prado #named
MOGACAR: A Method for Filtering Interesting Classification Association Rules (DBP), pp. 172–183.
SEKESEKE-2015-TaheriS #agile #development
A Feature-Based Tool-Selection Classification for Agile Software Development (MT, SMS), pp. 700–704.
SEKESEKE-2015-YangL #identification #requirements
Identification and Classification of Requirements from App User Reviews (HY, PL), pp. 7–12.
SIGIRSIGIR-2015-CanutoGSRM #approach #documentation #parallel #performance #scalability
An Efficient and Scalable MetaFeature-based Document Classification Approach based on Massively Parallel Computing (SDC, MAG, WS, TR, WM), pp. 333–342.
SIGIRSIGIR-2015-EswaranBP #modelling #scalability #topic
Modeling Website Topic Cohesion at Scale to Improve Webpage Classification (DE, PNB, JJPI), pp. 787–790.
SIGIRSIGIR-2015-FangOHML #topic #twitter
Topic-centric Classification of Twitter User’s Political Orientation (AF, IO, PH, CM, NL), pp. 791–794.
SIGIRSIGIR-2015-SallesGRR #automation #effectiveness #fault #named #random
BROOF: Exploiting Out-of-Bag Errors, Boosting and Random Forests for Effective Automated Classification (TS, MAG, VR, LCdR), pp. 353–362.
ASEASE-2015-ChoetkiertikulD #predict #using
Predicting Delays in Software Projects Using Networked Classification (T) (MC, HKD, TT, AG), pp. 353–364.
ASEASE-2015-GuzmanEB #approach #evolution #overview
Ensemble Methods for App Review Classification: An Approach for Software Evolution (N) (EG, MEH, BB), pp. 771–776.
ICSEICSE-v1-2015-GhotraMH #fault #modelling #performance #predict
Revisiting the Impact of Classification Techniques on the Performance of Defect Prediction Models (BG, SM, AEH), pp. 789–800.
ICSEICSE-v1-2015-PetrosyanRM #api #information management #using
Discovering Information Explaining API Types Using Text Classification (GP, MPR, RDM), pp. 869–879.
SACSAC-2015-BerardiEF0 #mobile #multi
Multi-store metadata-based supervised mobile app classification (GB, AE, TF, FS), pp. 585–588.
SACSAC-2015-BurkhardtK #multi #on the
On the spectrum between binary relevance and classifier chains in multi-label classification (SB, SK), pp. 885–892.
SACSAC-2015-CharuvakaR #approximate #coordination #scalability
Approximate block coordinate descent for large scale hierarchical classification (AC, HR), pp. 837–844.
SACSAC-2015-GomesBE #data type #learning
Pairwise combination of classifiers for ensemble learning on data streams (HMG, JPB, FE), pp. 941–946.
SACSAC-2015-GonzalezRP #image
Computationally-efficient classification of HEp-2 cell patterns in IIF images (LFPG, DDAR, MSP), pp. 825–830.
SACSAC-2015-MakrisVV #predict
Classification model for predicting cost slippage in governmental ICT projects (CM, PV, JV), pp. 1238–1241.
SACSAC-2015-OmatuYI #learning #smell
Smell classification of wines by the learning vector quantization method (SO, MY, YI), pp. 195–200.
SACSAC-2015-RochaRCOMVADGF #algorithm #dataset #documentation #named #performance #using
G-KNN: an efficient document classification algorithm for sparse datasets on GPUs using KNN (LCdR, GSR, RC, RSO, DM, FV, GA, SD, MAG, RF), pp. 1335–1338.
SACSAC-2015-TakemuraTT #twitter
Classification of Twitter follow links based on the followers’ intention (HT, AT, KT), pp. 1174–1180.
DACDAC-2015-ChenCX #named #power management #video
DaTuM: dynamic tone mapping technique for OLED display power saving based on video classification (XC, YC, CJX), p. 6.
DACDAC-2015-VenkataramaniRL #energy #machine learning
Scalable-effort classifiers for energy-efficient machine learning (SV, AR, JL, MS), p. 6.
DATEDATE-2015-OyaSYT #identification
A score-based classification method for identifying hardware-trojans at gate-level netlists (MO, YS, MY, NT), pp. 465–470.
HPCAHPCA-2015-RosDK #clustering #performance
Hierarchical private/shared classification: The key to simple and efficient coherence for clustered cache hierarchies (AR, MD, SK), pp. 186–197.
ISSTAISSTA-2015-XueWLXSC #behaviour #detection #javascript #modelling
Detection and classification of malicious JavaScript via attack behavior modelling (YX, JW, YL, HX, JS, MC), pp. 48–59.
DocEngDocEng-2014-DiemKS #analysis #documentation
Ruling analysis and classification of torn documents (MD, FK, RS), pp. 63–72.
DRRDRR-2014-KleberDS #retrieval #using #word
Form classification and retrieval using bag of words with shape features of line structures (FK, MD, RS), pp. 902107–9.
DRRDRR-2014-YouADT #image #retrieval
A contour-based shape descriptor for biomedical image classification and retrieval (DY, SA, DDF, GRT), p. ?–12.
HTHT-2014-TanakaTT #twitter #why
Why you follow: a classification scheme for twitter follow links (AT, HT, KT), pp. 324–326.
JCDLJCDL-2014-ChoiLD #automation #using #what
What is this song about anyway?: Automatic classification of subject using user interpretations and lyrics (KC, JHL, JSD), pp. 453–454.
JCDLJCDL-2014-TakanoSIHT #analysis #behaviour #documentation #towards
Microscopic analysis of document handling while reading: Classification of behavior toward paper document (KT, HS, JI, TH, ST), pp. 445–446.
VLDBVLDB-2014-SunRYD #crowdsourcing #machine learning #named #scalability #using
Chimera: Large-Scale Classification using Machine Learning, Rules, and Crowdsourcing (CS, NR, FY, AD), pp. 1529–1540.
VLDBVLDB-2014-YuYWLC #big data #design #detection #power management
Big Data Small Footprint: The Design of A Low-Power Classifier for Detecting Transportation Modes (MCY, TY, SCW, CJL, EYC), pp. 1429–1440.
EDMEDM-2014-Ezen-CanB14a
A Preliminary Investigation of Learner Characteristics for Unsupervised Dialogue Act Classification (AEC, KEB), pp. 373–374.
EDMEDM-2014-SilvaPC #predict #video
A Predictive Model for Video Lectures Classification (PS, RP, EC), pp. 325–326.
ITiCSEITiCSE-2014-TedreBMC #concept #education #identification #towards
Towards identification and classification of core and threshold concepts in methodology education in computing (MT, DB, SMB, JCC), pp. 237–242.
ICPCICPC-2014-ThungLOC #design #diagrams #metric #network #using
Condensing class diagrams by analyzing design and network metrics using optimistic classification (FT, DL, MHO, MRVC), pp. 110–121.
ICSMEICSME-2014-ZhouTGG #data mining #debugging #mining
Combining Text Mining and Data Mining for Bug Report Classification (YZ, YT, RG, HCG), pp. 311–320.
MSRMSR-2014-KochharLL #debugging #locality #question
It’s not a bug, it’s a feature: does misclassification affect bug localization? (PSK, TDBL, DL), pp. 296–299.
CHICHI-2014-LiuCBLM #navigation
Effects of display size and navigation type on a classification task (CL, OC, MBL, EL, WEM), pp. 4147–4156.
CHICHI-2014-SchwarzXMHH #probability #using
Probabilistic palm rejection using spatiotemporal touch features and iterative classification (JS, RX, JM, SEH, CH), pp. 2009–2012.
CSCWCSCW-2014-MillerGS #collaboration #visualisation
Unsupervised classification and visualization of unstructured text for the support of interdisciplinary collaboration (LJM, RG, SS), pp. 1033–1042.
HCIDHM-2014-IkenoboKKTG
The Classification Tendency and Common Denomination of the Points Paid Attention in Ikebana Instruction (YI, NK, NK, YT, AG), pp. 263–272.
HCIHIMI-DE-2014-Banic #interactive #visualisation
Selection Classification for Interaction with Immersive Volumetric Visualizations (AUB), pp. 10–21.
HCILCT-NLE-2014-TaraghiSES #learning #markov #multi
Markov Chain and Classification of Difficulty Levels Enhances the Learning Path in One Digit Multiplication (BT, AS, ME, MS), pp. 322–333.
HCISCSM-2014-MendesFFC #analysis #how #social #using
How Do Users Express Their Emotions Regarding the Social System in Use? A Classification of Their Postings by Using the Emotional Analysis of Norman (MSM, EF, VF, MFdC), pp. 229–241.
VISSOFTVISSOFT-2014-DanielWSSL #dependence #named #visualisation
Polyptychon: A Hierarchically-Constrained Classified Dependencies Visualization (DTD, EW, KS, MS, PL), pp. 83–86.
ICEISICEIS-v1-2014-0001DFL #constraints #documentation #process
Service Level Agreement Constraints into Processes for Document Classification (MB, MD, FF, AL), pp. 545–550.
CIKMCIKM-2014-CanutoSGRRGRM #effectiveness #on the #performance
On Efficient Meta-Level Features for Effective Text Classification (SDC, TS, MAG, LCdR, GSR, LG, TCR, WSM), pp. 1709–1718.
CIKMCIKM-2014-ChanDYTZ #ranking #retrieval
Term Selection and Result Reranking for Question Retrieval by Exploiting Hierarchical Classification (WC, JD, WY, JT, XZ), pp. 141–150.
CIKMCIKM-2014-HanWP #using
Within-Network Classification Using Radius-Constrained Neighborhood Patterns (JH, JRW, JP), pp. 1539–1548.
CIKMCIKM-2014-HongBH #framework #multi
A Mixtures-of-Trees Framework for Multi-Label Classification (CH, IB, MH), pp. 211–220.
CIKMCIKM-2014-LinLYC #modelling #sentiment
Exploring Ensemble of Models in Taxonomy-based Cross-Domain Sentiment Classification (CKL, YYL, CHY, HHC), pp. 1279–1288.
CIKMCIKM-2014-LiuLK #information management #performance #using
Using Local Information to Significantly Improve Classification Performance (WL, DL, RK), pp. 1947–1950.
CIKMCIKM-2014-LiZLW #probability
Probabilistic Classifier Chain Inference via Gibbs Sampling (LL, LZ, GL, HW), pp. 1855–1858.
CIKMCIKM-2014-LuciaF #knowledge-based #named #network
EgoCentric: Ego Networks for Knowledge-based Short Text Classification (WL, EF), pp. 1079–1088.
CIKMCIKM-2014-MaoWHO #learning #linear #multi
Nonlinear Classification via Linear SVMs and Multi-Task Learning (XM, OW, WH, PO), pp. 1955–1958.
CIKMCIKM-2014-WangWLW #concept #ranking
Concept-based Short Text Classification and Ranking (FW, ZW, ZL, JRW), pp. 1069–1078.
ECIRECIR-2014-KimJHLY #automation
Quality-Based Automatic Classification for Presentation Slides (SK, WJ, KH, JGL, MYY), pp. 638–643.
ECIRECIR-2014-LuoGWL #algorithm #named #network #novel
HetPathMine: A Novel Transductive Classification Algorithm on Heterogeneous Information Networks (CL, RG, ZW, CL), pp. 210–221.
ECIRECIR-2014-McDonaldMOG #overview #perspective #towards
Towards a Classifier for Digital Sensitivity Review (GM, CM, IO, TG), pp. 500–506.
ICMLICML-c1-2014-LiL #multi
Condensed Filter Tree for Cost-Sensitive Multi-Label Classification (CLL, HTL), pp. 423–431.
ICMLICML-c1-2014-YangSX
The Coherent Loss Function for Classification (WY, MS, HX), pp. 37–45.
ICMLICML-c2-2014-BaiLS #framework #online
A Bayesian Framework for Online Classifier Ensemble (QB, HL, SS), pp. 1584–1592.
ICMLICML-c2-2014-EbanMG
Discrete Chebyshev Classifiers (EE, EM, AG), pp. 1233–1241.
ICMLICML-c2-2014-LiG #learning #representation #semantics
Latent Semantic Representation Learning for Scene Classification (XL, YG), pp. 532–540.
ICMLICML-c2-2014-LinDH0 #encoding #multi
Multi-label Classification via Feature-aware Implicit Label Space Encoding (ZL, GD, MH, JW), pp. 325–333.
ICMLICML-c2-2014-RodriguesPR #learning #multi #process
Gaussian Process Classification and Active Learning with Multiple Annotators (FR, FCP, BR), pp. 433–441.
ICMLICML-c2-2014-SunIM #learning #linear
Learning Mixtures of Linear Classifiers (YS, SI, AM), pp. 721–729.
ICPRICPR-2014-AliNB #constraints #image #probability #scalability
Boosting Stochastic Newton with Entropy Constraint for Large-Scale Image Classification (WBHA, RN, MB), pp. 232–237.
ICPRICPR-2014-AndreuLMG #analysis #automation #gender #image
Analysis of the Effect of Image Resolution on Automatic Face Gender Classification (YA, JLC, RAM, PGS), pp. 273–278.
ICPRICPR-2014-BagheriGE #approach #novel #subclass
Generic Subclass Ensemble: A Novel Approach to Ensemble Classification (MAB, QG, SE), pp. 1254–1259.
ICPRICPR-2014-BagheriHGE #framework #multi #recognition
A Framework of Multi-classifier Fusion for Human Action Recognition (MAB, GH, QG, SE), pp. 1260–1265.
ICPRICPR-2014-BanerjeeCM #automation #game studies #generative #wiki
Playscript Classification and Automatic Wikipedia Play Articles Generation (SB, CC, PM), pp. 3630–3635.
ICPRICPR-2014-BargiXP #adaptation #infinity #learning #online #segmentation #streaming
An Infinite Adaptive Online Learning Model for Segmentation and Classification of Streaming Data (AB, RYDX, MP), pp. 3440–3445.
ICPRICPR-2014-BhattacharyaGC #estimation
Test Point Specific k Estimation for kNN Classifier (GB, KG, ASC), pp. 1478–1483.
ICPRICPR-2014-BougueliaBB #data type #detection #novel #performance
Efficient Active Novel Class Detection for Data Stream Classification (MRB, YB, AB), pp. 2826–2831.
ICPRICPR-2014-BouillonA #evolution #gesture #learning #online
Supervision Strategies for the Online Learning of an Evolving Classifier for Gesture Commands (MB, ÉA), pp. 2029–2034.
ICPRICPR-2014-ByeonLB #2d #network #using
Texture Classification Using 2D LSTM Networks (WB, ML, TMB), pp. 1144–1149.
ICPRICPR-2014-CaoHS #approach #kernel #learning #multi
Optimization-Based Extreme Learning Machine with Multi-kernel Learning Approach for Classification (LlC, WbH, FS), pp. 3564–3569.
ICPRICPR-2014-Cevikalp
2-Sided Best Fitting Hyperplane Classifier (HC), pp. 226–231.
ICPRICPR-2014-ChenCF #approach #hybrid #semantics
A Hybrid Holistic/Semantic Approach for Scene Classification (ZC, ZC, HF), pp. 2299–2304.
ICPRICPR-2014-CheplyginaSTPLB #learning #multi
Classification of COPD with Multiple Instance Learning (VC, LS, DMJT, JJHP, ML, MdB), pp. 1508–1513.
ICPRICPR-2014-CordellaSFF #random #reliability
Random Forest for Reliable Pre-classification of Handwritten Characters (LPC, CDS, FF, ASdF), pp. 1319–1324.
ICPRICPR-2014-Dahllof
Scribe Attribution for Early Medieval Handwriting by Means of Letter Extraction and Classification and a Voting Procedure for Larger Pieces (MD), pp. 1910–1915.
ICPRICPR-2014-DongPHLDJ #network #using
Vehicle Type Classification Using Unsupervised Convolutional Neural Network (ZD, MP, YH, TL, YD, YJ), pp. 172–177.
ICPRICPR-2014-DornaikaBSR #encoding #graph #locality
Locality Constrained Encoding Graph Construction and Application to Outdoor Object Classification (FD, AB, HS, YR), pp. 2483–2488.
ICPRICPR-2014-DuHZWD #case study #design #network #online #recognition #using
A Study of Designing Compact Classifiers Using Deep Neural Networks for Online Handwritten Chinese Character Recognition (JD, JSH, BZ, SW, LRD), pp. 2950–2955.
ICPRICPR-2014-El-GaalyTE
Spatial-Visual Label Propagation for Local Feature Classification (TEG, MT, AME), pp. 3422–3427.
ICPRICPR-2014-EnsafiLKT #automation #image
Automatic CAD System for HEp-2 Cell Image Classification (SE, SL, AAK, CLT), pp. 3321–3326.
ICPRICPR-2014-FahadTR #clustering #process #recognition #smarttech #using
Activity Recognition in Smart Homes Using Clustering Based Classification (LGF, SFT, MR), pp. 1348–1353.
ICPRICPR-2014-FangZ #learning
Cross Domain Shared Subspace Learning for Unsupervised Transfer Classification (ZF, ZZ), pp. 3927–3932.
ICPRICPR-2014-Filippone #process #pseudo
Bayesian Inference for Gaussian Process Classifiers with Annealing and Pseudo-Marginal MCMC (MF), pp. 614–619.
ICPRICPR-2014-GadermayrHU #adaptation
Scale-Adaptive Texture Classification (MG, SH, AU), pp. 2643–2648.
ICPRICPR-2014-Garcia-OlallaAFG #statistics
Local Oriented Statistics Information Booster (LOSIB) for Texture Classification (OGO, EA, LFR, VGC), pp. 1114–1119.
ICPRICPR-2014-GavriilidisT #kernel #random #using
Random Walk Kernel Applications to Classification Using Support Vector Machines (VG, AT), pp. 3898–3903.
ICPRICPR-2014-Gonzalez-CastroDC #adaptation #using
Pixel Classification Using General Adaptive Neighborhood-Based Features (VGC, JD, VC), pp. 3750–3755.
ICPRICPR-2014-HadjadjiCG #multi
Multiple One-Class Classifier Combination for Multi-class Classification (BH, YC, YG), pp. 2832–2837.
ICPRICPR-2014-HafianePS #adaptation
Adaptive Median Binary Patterns for Texture Classification (AH, KP, GS), pp. 1138–1143.
ICPRICPR-2014-HafnerLUW
Bridging the Resolution Gap between Endoscope Types for a Colonic Polyp Classification (MH, ML, AU, GW), pp. 2739–2744.
ICPRICPR-2014-HavaeiJL #interactive #performance #segmentation
Efficient Interactive Brain Tumor Segmentation as Within-Brain kNN Classification (MH, PMJ, HL), pp. 556–561.
ICPRICPR-2014-HazelhoffCW #trade-off #word
Optimal Performance-Efficiency Trade-off for Bag of Words Classification of Road Signs (LBH, IMC, PHNdW), pp. 2996–3001.
ICPRICPR-2014-IosifidisTP #network
Semi-supervised Classification of Human Actions Based on Neural Networks (AI, AT, IP), pp. 1336–1341.
ICPRICPR-2014-JangLSK #automation #multi #using #video
Automatic Video Genre Classification Using Multiple SVM Votes (WDJ, CL, JYS, CSK), pp. 2655–2660.
ICPRICPR-2014-KangKYLD #documentation #image #network
Convolutional Neural Networks for Document Image Classification (LK, JK, PY, YL, DSD), pp. 3168–3172.
ICPRICPR-2014-KrawczykWC #clustering #fuzzy
Weighted One-Class Classifier Ensemble Based on Fuzzy Feature Space Partitioning (BK, MW, BC), pp. 2838–2843.
ICPRICPR-2014-LiDXWP #image #probability
Local Label Probability Propagation for Hyperspectral Image Classification (HL, JD, SX, LW, CP), pp. 4251–4256.
ICPRICPR-2014-LiHYGPJ #re-engineering
Locality-Constrained Sparse Reconstruction for Trajectory Classification (CL, ZH, QY, SG, LP, JJ), pp. 2602–2606.
ICPRICPR-2014-LiuCVC
Leaf Species Classification Based on a Botanical Shape Sub-classifier Strategy (HL, DC, LV, GC), pp. 1496–1501.
ICPRICPR-2014-LiuL0L #image #learning
Regularized Hierarchical Feature Learning with Non-negative Sparsity and Selectivity for Image Classification (BL, JL, XB, HL), pp. 4293–4298.
ICPRICPR-2014-LiYLYWH #multi #predict
Multi-view Based AdaBoost Classifier Ensemble for Class Prediction from Gene Expression Profiles (LL, ZY, JL, JY, HSW, GH), pp. 178–183.
ICPRICPR-2014-LovatoMCGB #2d #biology #named #sequence
S-BLOSUM: Classification of 2D Shapes with Biological Sequence Alignment (PL, AM, CC, AG, MB), pp. 2335–2340.
ICPRICPR-2014-McCarthyCO #image
The Contribution of Morphological Features in the Classification of Prostate Carcinoma in Digital Pathology Images (NM, PC, GO), pp. 3269–3273.
ICPRICPR-2014-NeumannHKKB #image
Erosion Band Features for Cell Phone Image Based Plant Disease Classification (MN, LH, BK, KK, CB), pp. 3315–3320.
ICPRICPR-2014-NguyenTHM #novel
A Novel Sphere-Based Maximum Margin Classification Method (PN, DT, XH, WM), pp. 620–624.
ICPRICPR-2014-NocetiO #graph #kernel #process
A Spectral Graph Kernel and Its Application to Collective Activities Classification (NN, FO), pp. 3892–3897.
ICPRICPR-2014-OuyedA #kernel
Feature Relevance for Kernel Logistic Regression and Application to Action Classification (OO, MSA), pp. 1325–1329.
ICPRICPR-2014-PerinaKB #array #kernel #using
Expression Microarray Data Classification Using Counting Grids and Fisher Kernel (AP, MK, MB), pp. 1770–1775.
ICPRICPR-2014-PillaiFR #learning #multi
Learning of Multilabel Classifiers (IP, GF, FR), pp. 3452–3456.
ICPRICPR-2014-PistocchiCBFC #3d #detection #kernel
Kernelized Structural Classification for 3D Dogs Body Parts Detection (SP, SC, SB, NF, RC), pp. 1993–1998.
ICPRICPR-2014-QianZX #multi #social
Boosted Multi-modal Supervised Latent Dirichlet Allocation for Social Event Classification (SQ, TZ, CX), pp. 1999–2004.
ICPRICPR-2014-RahmaniMHM #linear
Action Classification with Locality-Constrained Linear Coding (HR, AM, DQH, ASM), pp. 3511–3516.
ICPRICPR-2014-RavalTJ #encoding #evaluation #fault #performance #using
Efficient Evaluation of SVM Classifiers Using Error Space Encoding (NR, RVT, CVJ), pp. 4411–4416.
ICPRICPR-2014-RengarajanRA #estimation #metric
Motion Estimation and Classification in Compressive Sensing from Dynamic Measurements (VR, ANR, RA), pp. 3475–3480.
ICPRICPR-2014-RenYZH #image #learning #nearest neighbour
Learning Convolutional Nonlinear Features for K Nearest Neighbor Image Classification (WR, YY, JZ, KH), pp. 4358–4363.
ICPRICPR-2014-SamantaC #using
Indian Classical Dance Classification on Manifold Using Jensen-Bregman LogDet Divergence (SS, BC), pp. 4507–4512.
ICPRICPR-2014-SatoKSK #learning #multi
Learning Multiple Complex Features Based on Classification Results (YS, KK, YS, MK), pp. 3369–3373.
ICPRICPR-2014-Saux #design #interactive
Interactive Design of Object Classifiers in Remote Sensing (BLS), pp. 2572–2577.
ICPRICPR-2014-SicreJ #image
Discovering and Aligning Discriminative Mid-level Features for Image Classification (RS, FJ), pp. 1975–1980.
ICPRICPR-2014-SlavkovikjVNHW
Image-Based Road Type Classification (VS, SV, WDN, SVH, RVdW), pp. 2359–2364.
ICPRICPR-2014-SousaSB #case study #set
Time Series Transductive Classification on Imbalanced Data Sets: An Experimental Study (CARdS, VMAdS, GEAPAB), pp. 3780–3785.
ICPRICPR-2014-SouzaSB
Extracting Texture Features for Time Series Classification (VMAdS, DFS, GEAPAB), pp. 1425–1430.
ICPRICPR-2014-TabiaV #3d #using
3D Shape Classification Using Information Fusion (HT, NSV), pp. 297–302.
ICPRICPR-2014-TerissiPG #random #using
Lip Reading Using Wavelet-Based Features and Random Forests Classification (LDT, MP, JCG), pp. 791–796.
ICPRICPR-2014-VilaltaGM #adaptation
Domain Adaptation under Data Misalignment: An Application to Cepheid Variable Star Classification (RV, KDG, LM), pp. 3660–3665.
ICPRICPR-2014-WangT
Label-Denoising Auto-encoder for Classification with Inaccurate Supervision Information (DW, XT), pp. 3648–3653.
ICPRICPR-2014-WenLWCW #feature model #robust
Optimal Feature Selection for Robust Classification via l2, 1-Norms Regularization (JW, ZL, WKW, JC, MW), pp. 517–521.
ICPRICPR-2014-Xiang0L #hybrid #image
Local Hybrid Coding for Image Classification (WX, JW, ML), pp. 3744–3749.
ICPRICPR-2014-XuSLPT #video
Graphics and Scene Text Classification in Video (JX, PS, TL, TQP, CLT), pp. 4714–4719.
ICPRICPR-2014-XuSLT #2d #3d #video
2D and 3D Video Scene Text Classification (JX, PS, TL, CLT), pp. 2932–2937.
ICPRICPR-2014-YamashitaW #using
k-NN Classification of Handwritten Characters Using a New Distortion-Tolerant Matching Measure (YY, TW), pp. 262–267.
ICPRICPR-2014-YangLTSG
Shape-Based Classification of Environmental Microorganisms (CY, CL, OT, KS, MG), pp. 3374–3379.
ICPRICPR-2014-YanHCCC #representation
PLSA-Based Sparse Representation for Object Classification (YY, JWH, HFC, SCC, DYC), pp. 1295–1300.
ICPRICPR-2014-YanSRLS #interactive #learning #multi
Evaluating Multi-task Learning for Multi-view Head-Pose Classification in Interactive Environments (YY, RS, ER, OL, NS), pp. 4182–4187.
ICPRICPR-2014-YiMHP #invariant #locality #multi #process
Pose Invariant Activity Classification for Multi-floor Indoor Localization (SY, PWM, TKH, VP), pp. 3505–3510.
ICPRICPR-2014-YinYPH #case study #learning
Shallow Classification or Deep Learning: An Experimental Study (XCY, CY, WYP, HWH), pp. 1904–1909.
ICPRICPR-2014-YuanT #algorithm #image #multi
Multi-scale Tensor l1-Based Algorithm for Hyperspectral Image Classification (HY, YYT), pp. 1383–1388.
ICPRICPR-2014-ZhangQWL #learning #online
Object Classification in Traffic Scene Surveillance Based on Online Semi-supervised Active Learning (ZZ, JQ, YW, ML), pp. 3086–3091.
ICPRICPR-2014-ZhaoSJ #markov
Coupled Hidden Markov Model for Electrocorticographic Signal Classification (RZ, GS, QJ), pp. 1858–1862.
ICPRICPR-2014-ZhuYCTJYZ #adaptation #hybrid
A Noise-Robust Adaptive Hybrid Pattern for Texture Classification (ZZ, XY, CLPC, DT, XJ, FY, JZ), pp. 1633–1638.
KDDKDD-2014-Aggarwal #problem
The setwise stream classification problem (CCA), pp. 432–441.
KDDKDD-2014-ChenCW #performance #scalability
Fast flux discriminant for large-scale sparse nonlinear classification (WC, YC, KQW), pp. 621–630.
KDDKDD-2014-PrabhuV #learning #multi #named #performance
FastXML: a fast, accurate and stable tree-classifier for extreme multi-label learning (YP, MV), pp. 263–272.
KDDKDD-2014-TsaiLL #incremental #linear
Incremental and decremental training for linear classification (CHT, CYL, CJL), pp. 343–352.
KDDKDD-2014-VasishtDVK #learning #multi
Active learning for sparse bayesian multilabel classification (DV, ACD, MV, AK), pp. 472–481.
KDDKDD-2014-ZhouL #mining #multi #network
Activity-edge centric multi-label classification for mining heterogeneous information networks (YZ, LL), pp. 1276–1285.
KDIRKDIR-2014-AbdallahI #modelling #n-gram #using #web
URL-based Web Page Classification — A New Method for URL-based Web Page Classification Using n-Gram Language Models (TAA, BdlI), pp. 14–21.
KDIRKDIR-2014-AlahmadiJM #concept #representation #using
Arabic Text Classification using Bag-of-Concepts Representation (AA, AJ, AEM), pp. 374–380.
KDIRKDIR-2014-AzadM #consistency #fault #heuristic
“Misclassification Error” Greedy Heuristic to Construct Decision Trees for Inconsistent Decision Tables (MA, MJM), pp. 184–191.
KDIRKDIR-2014-DomeniconiMPS #category theory
Cross-domain Text Classification through Iterative Refining of Target Categories Representations (GD, GM, RP, CS), pp. 31–42.
KDIRKDIR-2014-HafethAC #analysis #case study
Text Analysis of User-Generated Contents for Health-care Applications — Case Study on Smoking Status Classification (DAH, AA, DC), pp. 242–249.
KDIRKDIR-2014-LiuF #analysis #sentiment #topic #web
Web Content Classification based on Topic and Sentiment Analysis of Text (SL, TF), pp. 300–307.
KDIRKDIR-2014-LiuF14a #analysis #n-gram #sentiment #similarity #web
Combining N-gram based Similarity Analysis with Sentiment Analysis in Web Content Classification (SL, TF), pp. 530–537.
KDIRKDIR-2014-MohammadiMBRA #graph #parametricity
A Noise Resilient and Non-parametric Graph-based Classifier (MM, SAM, EB, BR, AA), pp. 170–175.
KDIRKDIR-2014-OliveiraBSC #automation #clustering #twitter
Combining Clustering and Classification Approaches for Reducing the Effort of Automatic Tweets Classification (EO, HGB, MRS, PMC), pp. 465–472.
KDIRKDIR-2014-SatoNS #kernel #using
A Simple Classification Method for Class Imbalanced Data using the Kernel Mean (YS, KN, AS), pp. 327–334.
KDIRKDIR-2014-TisserantRP #mining #semantics #statistics #twitter
Mining Tweet Data — Statistic and Semantic Information for Political Tweet Classification (GT, MR, VP), pp. 523–529.
KEODKEOD-2014-TriantafyllouA
Definition and Classification of Primitives for the Robotic Unfolding of a Piece of Clothing (DT, NAA), pp. 417–422.
KMISKMIS-2014-AngiusCMPS #semantics #social #web
Classification and Indexing of Web Content Based on a Model of Semantic Social Bookmarking (AA, GC, DM, FEP, GS), pp. 313–318.
KMISKMIS-2014-DinsoreanuB #sentiment #twitter
Unsupervised Twitter Sentiment Classification (MD, AB), pp. 220–227.
MLDMMLDM-2014-AlbarrakCZ #image #taxonomy
Dictionary Learning-Based Volumetric Image Classification for the Diagnosis of Age-Related Macular Degeneration (AA, FC, YZ), pp. 272–284.
MLDMMLDM-2014-AlshdaifatCD #multi
A Multi-path Strategy for Hierarchical Ensemble Classification (EA, FC, KD), pp. 198–212.
MLDMMLDM-2014-AnanpiriyakulPV #multi
Label Correction Strategy on Hierarchical Multi-Label Classification (TA, PP, PV), pp. 213–227.
MLDMMLDM-2014-FuMD #multi #network #performance #towards
Towards the Efficient Recovery of General Multi-Dimensional Bayesian Network Classifier (SF, SM, MCD), pp. 16–30.
MLDMMLDM-2014-JavedA #dataset #network #social #using
Creation of Bi-lingual Social Network Dataset Using Classifiers (IJ, HA), pp. 523–533.
MLDMMLDM-2014-LarinSKKHC #parametricity #representation #using
Parametric Representation of Objects in Color Space Using One-Class Classifiers (AL, OS, AK, SYK, SCH, BHC), pp. 300–314.
MLDMMLDM-2014-MaliarskyAH
A Neuro-Genetic System for Cardiac Arrhythmia Classification (EM, MA, MH), pp. 343–360.
MLDMMLDM-2014-Manzanilla-SalazarEG #clustering #fault
Minimizing Cluster Errors in LP-Based Nonlinear Classification (OMS, JEK, UMGP), pp. 163–174.
MLDMMLDM-2014-MountassirBB #algorithm #documentation #representation
The Nearest Centroid Based on Vector Norms: A New Classification Algorithm for a New Document Representation Model (AM, HB, IB), pp. 442–456.
MLDMMLDM-2014-PirasG #generative #image #roadmap
Open Issues on Codebook Generation in Image Classification Tasks (LP, GG), pp. 328–342.
MLDMMLDM-2014-Schafer #preprocessor #towards
Towards Time Series Classification without Human Preprocessing (PS), pp. 228–242.
MLDMMLDM-2014-UtkinZC #data-driven #database #robust
A Robust One-Class Classification Model with Interval-Valued Data Based on Belief Functions and Minimax Strategy (LVU, YAZ, AIC), pp. 107–118.
MLDMMLDM-2014-WaiyamaiKSR #concept #data type #named
ACCD: Associative Classification over Concept-Drifting Data Streams (KW, TK, BS, TR), pp. 78–90.
MLDMMLDM-2014-WaiyamaiS #approach #dataset
A Cost-Sensitive Based Approach for Improving Associative Classification on Imbalanced Datasets (KW, PS), pp. 31–42.
SEKESEKE-2014-WangKN #fault #metric #performance #predict
Choosing the Best Classification Performance Metric for Wrapper-based Software Metric Selection for Defect Prediction (HW, TMK, AN), pp. 540–545.
SIGIRSIGIR-2014-BabbarPGA #approach #distributed #ranking #scalability
Re-ranking approach to classification in large-scale power-law distributed category systems (RB, IP, ÉG, MRA), pp. 1059–1062.
SIGIRSIGIR-2014-BingGLNW #predict #segmentation #web
Web page segmentation with structured prediction and its application in web page classification (LB, RG, WL, ZYN, HW), pp. 767–776.
SIGIRSIGIR-2014-HingmireC #approach #topic
Topic labeled text classification: a weakly supervised approach (SH, SC), pp. 385–394.
SIGIRSIGIR-2014-LiWRM #interactive #named #query #retrieval
ReQ-ReC: high recall retrieval with query pooling and interactive classification (CL, YW, PR, QM), pp. 163–172.
SIGIRSIGIR-2014-RenPLDR #multi #social
Hierarchical multi-label classification of social text streams (ZR, MHP, SL, WvD, MdR), pp. 213–222.
SIGIRSIGIR-2014-ZhangZ0LM #overview #sentiment
Do users rate or review?: boost phrase-level sentiment labeling with review-level sentiment classification (YZ, HZ, MZ, YL, SM), pp. 1027–1030.
MODELSMoDELS-2014-GomesBA #model transformation #pattern matching #tool support
Classification of Model Transformation Tools: Pattern Matching Techniques (CG, BB, VA), pp. 619–635.
SACSAC-2014-BarddalGE #concept #named #network #social
SFNClassifier: a scale-free social network method to handle concept drift (JPB, HMG, FE), pp. 786–791.
SACSAC-2014-ChoiSP #2d #correlation #distance #image #matrix
Matrix correlation distance for 2D image classification (HC, JS, HP), pp. 1741–1742.
SACSAC-2014-GomesE #adaptation #data type #named #social
SAE2: advances on the social adaptive ensemble classifier for data streams (HMG, FE), pp. 798–804.
SACSAC-2014-OmatuY #smell #using
Smell classification using weakly responding data (SO, MY), pp. 213–214.
SACSAC-2014-RossiLR #algorithm #network #using
A parameter-free label propagation algorithm using bipartite heterogeneous networks for text classification (RGR, AAL, SOR), pp. 79–84.
SACSAC-2014-SeelandMKK
Extracting information from support vector machines for pattern-based classification (MS, AM, AK, SK), pp. 129–136.
SACSAC-2014-SpiegelJA #distance #performance
Fast time series classification under lucky time warping distance (SS, BJJ, SA), pp. 71–78.
SACSAC-2014-ZangerleS #quote #twitter
“Sorry, I was hacked”: a classification of compromised twitter accounts (EZ, GS), pp. 587–593.
SACSAC-2014-ZimmermannNS #adaptation
Adaptive semi supervised opinion classifier with forgetting mechanism (MZ, EN, MS), pp. 805–812.
CASECASE-2014-MatsumotoY #3d #framework #image
An object classification framework based on unmeasurable area patterns found in 3D range images (KM, KY), pp. 242–248.
CASECASE-2014-WolffNLM #lifecycle #standard
An information classification system for life cycle and manufacturing standards (SW, AN, DL, KCM), pp. 498–503.
CASECASE-2014-Wu
Classifications for batch service queues in production systems (KW), pp. 698–703.
DACDAC-2014-AlbalawiLL #algorithm #design #fixpoint #implementation #machine learning #power management
Computer-Aided Design of Machine Learning Algorithm: Training Fixed-Point Classifier for On-Chip Low-Power Implementation (HA, YL, XL), p. 6.
PDPPDP-2014-GogolevM #network #random
Density Classification in Asynchronous Random Networks with Faulty Nodes (AG, LM), pp. 256–261.
PDPPDP-2014-MolinaFCP #hybrid #image
Hybrid Classification of Resistors through Image Processing (RM, PF, VGC, MP), pp. 103–106.
PDPPDP-2014-Zufferey #design #metaheuristic
Design and Classification of Ant Metaheuristics (NZ), pp. 339–343.
LICSLICS-CSL-2014-ChenM #complexity #graph #query
One hierarchy spawns another: graph deconstructions and the complexity classification of conjunctive queries (HC, MM), p. 10.
TAPTAP-2014-JannesariKSW #generative #parallel #testing
Generating Classified Parallel Unit Tests (AJ, NK, JS, FW), pp. 117–133.
ECSAECSA-2013-MiesbauerW #design #overview
Classification of Design Decisions — An Expert Survey in Practice (CM, RW), pp. 130–145.
DocEngDocEng-2013-VilaresAG #twitter
Supervised polarity classification of Spanish tweets based on linguistic knowledge (DV, MAA, CGR), pp. 169–172.
DRRDRR-2013-AriesON #algorithm #automation #clustering #summary #using
Using clustering and a modified classification algorithm for automatic text summarization (AA, HO, ON).
DRRDRR-2013-VasilopoulosK
A classification-free word-spotting system (NV, EK).
HTHT-2013-CanoVRCH #social #social media #topic
Harnessing linked knowledge sources for topic classification in social media (AEC, AV, MR, FC, YH), pp. 41–50.
HTHT-2013-RoutBPC #approach #social
Where’s @wally?: a classification approach to geolocating users based on their social ties (DPR, KB, DPP, TC), pp. 11–20.
ICDARICDAR-2013-AlvaroSB #hybrid #network #online
Classification of On-Line Mathematical Symbols with Hybrid Features and Recurrent Neural Networks (FA, JAS, JMB), pp. 1012–1016.
ICDARICDAR-2013-BaechlerLI #using
Text Line Extraction Using DMLP Classifiers for Historical Manuscripts (MB, ML, RI), pp. 1029–1033.
ICDARICDAR-2013-BougueliaBB #approach #documentation #learning
A Stream-Based Semi-supervised Active Learning Approach for Document Classification (MRB, YB, AB), pp. 611–615.
ICDARICDAR-2013-CecottiV #multi #recognition
Rejection Schemes in Multi-class Classification — Application to Handwritten Character Recognition (HC, SV), pp. 445–449.
ICDARICDAR-2013-ChengSAT #data fusion #image #using #visual notation
Graphical Figure Classification Using Data Fusion for Integrating Text and Image Features (BC, RJS, SA, GRT), pp. 693–697.
ICDARICDAR-2013-GordoRKB #documentation #segmentation
Document Classification and Page Stream Segmentation for Digital Mailroom Applications (AG, MR, DK, ADB), pp. 621–625.
ICDARICDAR-2013-HigaH #image #recognition
Local Subspace Classifier with Transformation Invariance for Appearance-Based Character Recognition in Natural Images (KH, SH), pp. 533–537.
ICDARICDAR-2013-HoRRES #approach #documentation
Document Classification in a Non-stationary Environment: A One-Class SVM Approach (AKNH, NR, JYR, VE, NS), pp. 616–620.
ICDARICDAR-2013-HuC #pseudo #using #verification
Offline Signature Verification Using Real Adaboost Classifier Combination of Pseudo-dynamic Features (JH, YC), pp. 1345–1349.
ICDARICDAR-2013-ImpedovoMPBI #effectiveness #performance
Voronoi Tessellation for Effective and Efficient Handwritten Digit Classification (SI, FMM, GP, DB, DI), pp. 435–439.
ICDARICDAR-2013-KhayyatLS #verification #word
Verification of Hierarchical Classifier Results for Handwritten Arabic Word Spotting (MK, LL, CYS), pp. 572–576.
ICDARICDAR-2013-KimLT #heuristic #identification #using
Identification of Investigator Name Zones Using SVM Classifiers and Heuristic Rules (JK, DXL, GRT), pp. 140–144.
ICDARICDAR-2013-KumarD #documentation #image
Unsupervised Classification of Structurally Similar Document Images (JK, DSD), pp. 1225–1229.
ICDARICDAR-2013-LuoOWK #approach #automation #using
Automatic Chinese Text Classification Using Character-Based and Word-Based Approach (XL, WO, TW, FK), pp. 329–333.
ICDARICDAR-2013-Siriteerakul
Mixed Thai-English Character Classification Based on Histogram of Oriented Gradient Feature (TS), pp. 847–851.
ICDARICDAR-2013-SuTLDT #documentation #image #learning #representation
Self Learning Classification for Degraded Document Images by Sparse Representation (BS, ST, SL, TAD, CLT), pp. 155–159.
ICDARICDAR-2013-WeiBSI #analysis #documentation #evaluation #layout
Evaluation of SVM, MLP and GMM Classifiers for Layout Analysis of Historical Documents (HW, MB, FS, RI), pp. 1220–1224.
ICDARICDAR-2013-YanYWYYH #sorting
Sorting-Based Dynamic Classifier Ensemble Selection (YY, XCY, ZBW, XY, CY, HWH), pp. 673–677.
ICDARICDAR-2013-YuEC #online
Mental Workload Classification via Online Writing Features (KY, JE, FC), pp. 1110–1114.
PODSPODS-2013-ChenM #complexity #query
The fine classification of conjunctive queries and parameterized logarithmic space complexity (HC, MM), pp. 309–320.
VLDBVLDB-2013-GattaniLGTCDSRHD #approach #social #social media
Entity Extraction, Linking, Classification, and Tagging for Social Media: A Wikipedia-Based Approach (AG, DSL, NG, MT, XC, SD, SS, AR, VH, AD), pp. 1126–1137.
ICSMEICSM-2013-YukselS #analysis #automation #case study
Automated Classification of Static Code Analysis Alerts: A Case Study (UY, HS), pp. 532–535.
CHICHI-2013-WarrenLVG #flexibility #gesture
Bending the rules: bend gesture classification for flexible displays (KW, JL, VV, AG), pp. 607–610.
HCIHCI-AMTE-2013-MayasHK #diagrams #process
Extending the Information of Activity Diagrams with a User Input Classification (CM, SH, HK), pp. 391–400.
HCIHCI-III-2013-BockLSWW #automation
Audio-Based Pre-classification for Semi-automatic Facial Expression Coding (RB, KLE, IS, SW, AW), pp. 301–309.
HCIHCI-III-2013-RukavinaGTHWTJ #automation #gender
The Impact of Gender and Sexual Hormones on Automated Psychobiological Emotion Classification (SR, SG, JWT, DH, SW, HCT, LJB), pp. 474–482.
HCIHCI-III-2013-XuGC #kernel #representation
Kernel Based Weighted Group Sparse Representation Classifier (BX, PG, CLPC), pp. 236–245.
HCIHCI-III-2013-YinTWDWZ #image
Classification Based on LBP and SVM for Human Embryo Microscope Images (YbY, YT, WW, FD, ZW, MZ), pp. 280–288.
HCIHIMI-D-2013-YanagimotoSY #estimation #network #sentiment #using #word
Word Classification for Sentiment Polarity Estimation Using Neural Network (HY, MS, AY), pp. 669–677.
HCIHIMI-LCCB-2013-TachizawaOM #automation #overview
An Automatic Classification of Product Review into Given Viewpoints (YT, MO, HM), pp. 598–606.
HCIOCSC-2013-YuanOXS #overview #sentiment #using #web
Sentiment Classification of Web Review Using Association Rules (MY, YO, ZX, HS), pp. 442–450.
ICEISICEIS-v1-2013-CazzolatoRYS #algorithm #data type #statistics
A Statistical Decision Tree Algorithm for Data Stream Classification (MTC, MXR, CAY, MTPS), pp. 217–223.
ICEISICEIS-v1-2013-MoritaN #using
Classification Model using Contrast Patterns (HM, MN), pp. 334–339.
ICEISICEIS-v1-2013-QasimR #analysis #evaluation #linear #using
Classification of Hepatitis Patients and Fibrosis Evaluation using Decision Trees and Linear Discriminant Analysis (RQ, RMR), pp. 239–246.
CIKMCIKM-2013-BagdouriWLO #towards
Towards minimizing the annotation cost of certified text classification (MB, WW, DDL, DWO), pp. 989–998.
CIKMCIKM-2013-BaoCD #topic
A partially supervised cross-collection topic model for cross-domain text classification (YB, NC, AD), pp. 239–248.
CIKMCIKM-2013-ChanYTDZW #categorisation #community #kernel #topic
Community question topic categorization via hierarchical kernelized classification (WC, WY, JT, JD, XZ, WW), pp. 959–968.
CIKMCIKM-2013-ChenW #learning #scalability
Cost-sensitive learning for large-scale hierarchical classification (JC, DW), pp. 1351–1360.
CIKMCIKM-2013-GuoZ #comprehension #empirical #graph #perspective
Understanding the roles of sub-graph features for graph classification: an empirical study perspective (TG, XZ), pp. 817–822.
CIKMCIKM-2013-HachenbergG #clustering #documentation #locality #scalability #web
Locality sensitive hashing for scalable structural classification and clustering of web documents (CH, TG), pp. 359–368.
CIKMCIKM-2013-McDowellA #network
Labels or attributes?: rethinking the neighbors for collective classification in sparsely-labeled networks (LM, DWA), pp. 847–852.
CIKMCIKM-2013-SeverynNM #ranking
Building structures from classifiers for passage reranking (AS, MN, AM), pp. 969–978.
CIKMCIKM-2013-ZhangJSCDZ #detection
Short text classification by detecting information path (SZ, XJ, DS, BC, XD, XZ), pp. 727–732.
ECIRECIR-2013-ErmakovE #sentiment
Sentiment Classification Based on Phonetic Characteristics (SE, LE), pp. 706–709.
ECIRECIR-2013-FuNZWJZ
Classification of Opinion Questions (HF, ZN, CZ, LW, PJ, JZ), pp. 714–717.
ECIRECIR-2013-JeongM #dependence #recognition #using
Using WordNet Hypernyms and Dependency Features for Phrasal-Level Event Recognition and Type Classification (YJ, SHM), pp. 267–278.
ECIRECIR-2013-JuM #incremental #ranking
Incremental Reranking for Hierarchical Text Classification (QJ, AM), pp. 726–729.
ECIRECIR-2013-JuMJ #learning #rank
Learning to Rank from Structures in Hierarchical Text Classification (QJ, AM, RJ), pp. 183–194.
ECIRECIR-2013-NeshatiAHB #network #social
A Joint Classification Method to Integrate Scientific and Social Networks (MN, EA, DH, HB), pp. 122–133.
ECIRECIR-2013-NguyenTT #learning #rank #using
Folktale Classification Using Learning to Rank (DN, DT, MT), pp. 195–206.
ECIRECIR-2013-PritsosS #automation #identification
Open-Set Classification for Automated Genre Identification (DAP, ES), pp. 207–217.
ICMLICML-c1-2013-ChevaleyreKZ #linear
Rounding Methods for Discrete Linear Classification (YC, FK, JDZ), pp. 651–659.
ICMLICML-c1-2013-HoJV #adaptation #crowdsourcing
Adaptive Task Assignment for Crowdsourced Classification (CJH, SJ, JWV), pp. 534–542.
ICMLICML-c1-2013-KolarL #feature model
Feature Selection in High-Dimensional Classification (MK, HL), pp. 329–337.
ICMLICML-c1-2013-PeleTGW #performance
The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear Classification (OP, BT, AG, MW), pp. 205–213.
ICMLICML-c1-2013-TorkamaniL
Convex Adversarial Collective Classification (MT, DL), pp. 642–650.
ICMLICML-c1-2013-XuKWC
Cost-Sensitive Tree of Classifiers (ZEX, MJK, KQW, MC), pp. 133–141.
ICMLICML-c2-2013-YangH #learning
Activized Learning with Uniform Classification Noise (LY, SH), pp. 370–378.
ICMLICML-c3-2013-BaktashmotlaghHBLS #analysis #video
Non-Linear Stationary Subspace Analysis with Application to Video Classification (MB, MTH, AB, BCL, MS), pp. 450–458.
ICMLICML-c3-2013-BiK #multi #performance
Efficient Multi-label Classification with Many Labels (WB, JTYK), pp. 405–413.
ICMLICML-c3-2013-CortesMR #kernel #multi
Multi-Class Classification with Maximum Margin Multiple Kernel (CC, MM, AR), pp. 46–54.
ICMLICML-c3-2013-DembczynskiJKWH #approach #multi #optimisation #plugin
Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization (KD, AJ, WK, WW, EH), pp. 1130–1138.
ICMLICML-c3-2013-DurrantK #bound #fault
Sharp Generalization Error Bounds for Randomly-projected Classifiers (RJD, AK), pp. 693–701.
ICMLICML-c3-2013-GermainHLM #adaptation #approach #linear
A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers (PG, AH, FL, EM), pp. 738–746.
ICMLICML-c3-2013-Izbicki #algebra #approach #online #parallel #performance
Algebraic classifiers: a generic approach to fast cross-validation, online training, and parallel training (MI), pp. 648–656.
ICMLICML-c3-2013-LongS #consistency #multi
Consistency versus Realizable H-Consistency for Multiclass Classification (PML, RAS), pp. 801–809.
ICMLICML-c3-2013-MenonNAC #algorithm #consistency #on the #statistics
On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance (AKM, HN, SA, SC), pp. 603–611.
ICMLICML-c3-2013-NguyenS #algorithm #optimisation
Algorithms for Direct 0-1 Loss Optimization in Binary Classification (TN, SS), pp. 1085–1093.
ICMLICML-c3-2013-PiresSG #bound #multi
Cost-sensitive Multiclass Classification Risk Bounds (BAP, CS, MG), pp. 1391–1399.
KDDKDD-2013-GopalY #dependence #recursion #scalability #visual notation
Recursive regularization for large-scale classification with hierarchical and graphical dependencies (SG, YY), pp. 257–265.
KDDKDD-2013-GuALH #graph
Selective sampling on graphs for classification (QG, CCA, JL, JH), pp. 131–139.
KDDKDD-2013-KongCY #correlation #mining #multi #network
Multi-label classification by mining label and instance correlations from heterogeneous information networks (XK, BC, PSY), pp. 614–622.
KDDKDD-2013-KongY #automation #distance #learning
Discriminant malware distance learning on structural information for automated malware classification (DK, GY), pp. 1357–1365.
KDDKDD-2013-SongLLY #collaboration #microblog #process
Collaborative boosting for activity classification in microblogs (YS, ZL, CWkL, QY), pp. 482–490.
KDDKDD-2013-ThorntonHHL #algorithm #named #optimisation
Auto-WEKA: combined selection and hyperparameter optimization of classification algorithms (CT, FH, HHH, KLB), pp. 847–855.
KDDKDD-2013-WangS #multi #relational #social #using
Multi-label relational neighbor classification using social context features (XW, GS), pp. 464–472.
KDDKDD-2013-YenCLLL #coordination #linear #memory management #scalability
Indexed block coordinate descent for large-scale linear classification with limited memory (IEHY, CFC, TWL, SWL, SDL), pp. 248–256.
KDIRKDIR-KMIS-2013-AlwazaePK #verification
Verifying the Usefulness of a Classification System of Best Practices (MMSA, EP, HK), pp. 405–412.
KDIRKDIR-KMIS-2013-CheetiSC #adaptation #approach #naive bayes #sentiment #syntax #using
Cross-domain Sentiment Classification using an Adapted Naïve Bayes Approach and Features Derived from Syntax Trees (SC, AS, DC), pp. 169–176.
KEODKEOD-2013-CostaFML #approach #information management #ontology #using
Classification of Knowledge Representations using an Ontology-based Approach (RC, PF, PMNM, CL), pp. 184–191.
MLDMMLDM-2013-BijaksanaLA
A Pattern Based Two-Stage Text Classifier (MAB, YL, AA), pp. 169–182.
MLDMMLDM-2013-CastroSAE #automation #database #using #web
Automatic Classification of Web Databases Using Domain-Dictionaries (HMMC, VJSS, ILA, HJEB), pp. 340–351.
MLDMMLDM-2013-DincA #evaluation #image #random #using
Evaluation of Hyperspectral Image Classification Using Random Forest and Fukunaga-Koontz Transform (SD, RSA), pp. 234–245.
MLDMMLDM-2013-DoanDP #scalability #visual notation
Large Scale Visual Classification with Many Classes (TND, TND, FP), pp. 629–643.
MLDMMLDM-2013-EichelbergerS #empirical #multi
An Empirical Study of Reducing Multiclass Classification Methodologies (RKE, VSS), pp. 505–519.
MLDMMLDM-2013-KokkulaM #detection #synthesis #topic
Classification and Outlier Detection Based on Topic Based Pattern Synthesis (SK, NMM), pp. 99–114.
MLDMMLDM-2013-PrieditisL #bound #performance #problem #using
When Classification becomes a Problem: Using Branch-and-Bound to Improve Classification Efficiency (AP, ML), pp. 466–480.
MLDMMLDM-2013-SappP #clustering #predict
Accuracy-Based Classification EM: Combining Clustering with Prediction (SS, AP), pp. 458–465.
MLDMMLDM-2013-SigdelA #assessment #correlation #named
Pacc — A Discriminative and Accuracy Correlated Measure for Assessment of Classification Results (MS, RSA), pp. 281–295.
MLDMMLDM-2013-Suthaharan #big data #network
A Single-Domain, Representation-Learning Model for Big Data Classification of Network Intrusion (SS), pp. 296–310.
MLDMMLDM-2013-VavreckaL #feature model
EEG Feature Selection Based on Time Series Classification (MV, LL), pp. 520–527.
MLDMMLDM-2013-WilliamsHFR #distance #evaluation #probability
Area under the Distance Threshold Curve as an Evaluation Measure for Probabilistic Classifiers (SW, MH, JDF, DSR), pp. 644–657.
SEKESEKE-2013-AlviD #fuzzy #image #using
Image Steganography Using Fuzzy Domain Transformation and Pixel Classification (AKA, RD), pp. 277–282.
SEKESEKE-2013-KarimM #performance
Revisiting the Performance of Weighted k-Nearest Centroid Neighbor Classifiers (MRK, MM), pp. 332–337.
SIGIRSIGIR-2013-BalogR #cumulative #ranking #recommendation
Cumulative citation recommendation: classification vs. ranking (KB, HR), pp. 941–944.
SIGIRSIGIR-2013-HingmireCPC #documentation #topic
Document classification by topic labeling (SH, SC, GKP, SC), pp. 877–880.
SIGIRSIGIR-2013-WebberBLO #effectiveness #evaluation #testing
Sequential testing in classifier evaluation yields biased estimates of effectiveness (WW, MB, DDL, DWO), pp. 933–936.
SIGIRSIGIR-2013-WebberP
Assessor disagreement and text classifier accuracy (WW, JP), pp. 929–932.
SIGIRSIGIR-2013-YamamotoN #music #video
Leveraging viewer comments for mood classification of music video clips (TY, SN), pp. 797–800.
POPLPOPL-2013-LivshitsC #automation #security #towards
Towards fully automatic placement of security sanitizers and declassifiers (BL, SC), pp. 385–398.
ASEASE-2013-NguyenT #automation #combinator #dependence #testing
Automated inference of classifications and dependencies for combinatorial testing (DCN, PT), pp. 622–627.
ICSEICSE-2013-HerzigJZ #debugging #how #predict
It’s not a bug, it’s a feature: how misclassification impacts bug prediction (KH, SJ, AZ), pp. 392–401.
SACSAC-2013-AkritidisB #algorithm #machine learning #research
A supervised machine learning classification algorithm for research articles (LA, PB), pp. 115–120.
SACSAC-2013-BifetPRH #adaptation #data type #performance #probability
Efficient data stream classification via probabilistic adaptive windows (AB, BP, JR, GH), pp. 801–806.
SACSAC-2013-BlondelSU #constraints #learning #using
Learning non-linear classifiers with a sparsity constraint using L1 regularization (MB, KS, KU), pp. 167–169.
SACSAC-2013-PapadakisT #mutation testing #testing #using
Mutation testing strategies using mutant classification (MP, YLT), pp. 1223–1229.
DACDAC-2013-YuLJC #detection #feature model #using
Machine-learning-based hotspot detection using topological classification and critical feature extraction (YTY, GHL, IHRJ, CC), p. 6.
DATEDATE-2013-BraojosAA #embedded #random #using
A methodology for embedded classification of heartbeats using random projections (RB, GA, DA), pp. 899–904.
ICSTICST-2013-NairVSB #assessment #overview #perspective #safety
Classification, Structuring, and Assessment of Evidence for Safety — A Systematic Literature Review (SN, JLdlV, MS, LCB), pp. 94–103.
VMCAIVMCAI-2013-SlabyST #database #named
ClabureDB: Classified Bug-Reports Database (JS, JS, MT), pp. 268–274.
DocEngDocEng-2012-KimHKL #library
Scientific table type classification in digital library (SK, KH, SYK, YL), pp. 133–136.
DRRDRR-2012-ChengWAST #algorithm #image #optimisation #visual notation
Graphical image classification combining an evolutionary algorithm and binary particle swarm optimization (BC, RW, SA, RJS, GRT).
DRRDRR-2012-KimLT #identification
Combining SVM classifiers to identify investigator name zones in biomedical articles (JK, DXL, GRT).
DRRDRR-2012-Obafemi-AjayiAX #documentation
Ensemble methods with simple features for document zone classification (TOA, GA, BX).
DRRDRR-2012-RamaiahKG #documentation
Handwritten document age classification based on handwriting styles (CR, GK, VG).
JCDLJCDL-2012-LeeH #generative #music #using
Generating ground truth for music mood classification using mechanical turk (JHL, XH), pp. 129–138.
PODSPODS-2012-KostylevRS #query
Classification of annotation semirings over query containment (EVK, JLR, AZS), pp. 237–248.
TPDLTPDL-2012-SumbanaGSAV #automation #detection #wiki
Automatic Vandalism Detection in Wikipedia with Active Associative Classification (MS, MAG, RSO, JMA, AV), pp. 138–143.
ICSMEICSM-2012-PrasetyoLATL #automation #microblog
Automatic classification of software related microblogs (PKP, DL, PA, YT, EPL), pp. 596–599.
WCREWCRE-2012-TianLS #debugging #fine-grained #information retrieval #nearest neighbour #predict
Information Retrieval Based Nearest Neighbor Classification for Fine-Grained Bug Severity Prediction (YT, DL, CS), pp. 215–224.
CoGCIG-2012-MachadoPC #approach #automation #modelling
A binary classification approach for automatic preference modeling of virtual agents in Civilization IV (MCM, GLP, LC), pp. 155–162.
CSCWCSCW-2012-ChoudhuryDN #category theory #twitter
Unfolding the event landscape on twitter: classification and exploration of user categories (MDC, ND, MN), pp. 241–244.
ICEISICEIS-v3-2012-HamadaASO #documentation #taxonomy #using
A Classification Method of Open-ended Questionnaires using Category-based Dictionary from Sampled Documents (KH, MA, MS, HO), pp. 193–198.
ICEISICEIS-v3-2012-TsudaASO #automation
A Classification Method of Inquiry e-Mails for Describing FAQ with Automatic Setting Mechanism of Judgment Threshold Values (YT, MA, MS, HO), pp. 199–205.
CIKMCIKM-2012-AwadallahRW #named
PolariCQ: polarity classification of political quotations (RA, MR, GW), pp. 1945–1949.
CIKMCIKM-2012-BabbarPGA #empirical #on the #scalability #trade-off
On empirical tradeoffs in large scale hierarchical classification (RB, IP, ÉG, CA), pp. 2299–2302.
CIKMCIKM-2012-BaeK #effectiveness #recommendation
An effective category classification method based on a language model for question category recommendation on a cQA service (KB, YK), pp. 2255–2258.
CIKMCIKM-2012-ChengZXAC #learning #on the
On active learning in hierarchical classification (YC, KZ, YX, AA, ANC), pp. 2467–2470.
CIKMCIKM-2012-ChenW #automation #naive bayes
Automated feature weighting in naive bayes for high-dimensional data classification (LC, SW), pp. 1243–1252.
CIKMCIKM-2012-ChuaCBL #twitter
Community-based classification of noun phrases in twitter (FCTC, WWC, JB, EPL), pp. 1702–1706.
CIKMCIKM-2012-DuanWZS #graph #twitter
Graph-based collective classification for tweets (YD, FW, MZ, HYS), pp. 2323–2326.
CIKMCIKM-2012-EldardiryN #analysis #graph #how #predict
An analysis of how ensembles of collective classifiers improve predictions in graphs (HE, JN), pp. 225–234.
CIKMCIKM-2012-FukumotoYMS #documentation
Text classification with relatively small positive documents and unlabeled data (FF, TY, SM, YS), pp. 2315–2318.
CIKMCIKM-2012-JuLSZHL #documentation #sentiment #word
Dual word and document seed selection for semi-supervised sentiment classification (SJ, SL, YS, GZ, YH, XL), pp. 2295–2298.
CIKMCIKM-2012-KongYDW #network
Meta path-based collective classification in heterogeneous information networks (XK, PSY, YD, DJW), pp. 1567–1571.
CIKMCIKM-2012-LiangZ #performance
An efficient and simple under-sampling technique for imbalanced time series classification (GL, CZ), pp. 2339–2342.
CIKMCIKM-2012-LongCZZ #named #using
TCSST: transfer classification of short & sparse text using external data (GL, LC, XZ, CZ), pp. 764–772.
CIKMCIKM-2012-TakemuraT #twitter
Tweet classification based on their lifetime duration (HT, KT), pp. 2367–2370.
CIKMCIKM-2012-XuXLW
Coarse-to-fine sentence-level emotion classification based on the intra-sentence features and sentential context (JX, RX, QL, XW), pp. 2455–2458.
CIKMCIKM-2012-YaoS12a #web
A tag-centric discriminative model for web objects classification (LY, QZS), pp. 2247–2250.
CIKMCIKM-2012-ZerrSH #exclamation #image #privacy #retrieval
PicAlert!: a system for privacy-aware image classification and retrieval (SZ, SS, JSH), pp. 2710–2712.
CIKMCIKM-2012-ZhuCCXT #information management #mobile
Exploiting enriched contextual information for mobile app classification (HZ, HC, EC, HX, JT), pp. 1617–1621.
CIKMCIKM-2012-ZhuYCQ #approach #feature model #graph
Graph classification: a diversified discriminative feature selection approach (YZ, JXY, HC, LQ), pp. 205–214.
CIKMCIKM-2012-ZhuZYGX #parallel
Parallel proximal support vector machine for high-dimensional pattern classification (ZZ, XZ, YY, YFG, XX), pp. 2351–2354.
ECIRECIR-2012-DasMG #identification #topic
Phrase Pair Classification for Identifying Subtopics (SD, PM, CLG), pp. 489–493.
ECIRECIR-2012-Martinez-AlvarezYR #automation #documentation
Semi-automatic Document Classification: Exploiting Document Difficulty (MMA, SY, TR), pp. 468–471.
ECIRECIR-2012-VitaleFS #topic
Classification of Short Texts by Deploying Topical Annotations (DV, PF, US), pp. 376–387.
ICMLICML-2012-BelletHS #learning #linear #similarity
Similarity Learning for Provably Accurate Sparse Linear Classification (AB, AH, MS), p. 193.
ICMLICML-2012-Ben-DavidLSS #fault #using
Minimizing The Misclassification Error Rate Using a Surrogate Convex Loss (SBD, DL, NS, KS), p. 16.
ICMLICML-2012-Busa-FeketeBK #graph #performance #using
Fast classification using sparse decision DAGs (RBF, DB, BK), p. 99.
ICMLICML-2012-DenchevDVN #optimisation #quantum #robust
Robust Classification with Adiabatic Quantum Optimization (VSD, ND, SVNV, HN), p. 131.
ICMLICML-2012-GuoX #learning #multi
Cross Language Text Classification via Subspace Co-regularized Multi-view Learning (YG, MX), p. 120.
ICMLICML-2012-JoulinB
A convex relaxation for weakly supervised classifiers (AJ, FRB), p. 171.
ICMLICML-2012-KumarNKD #framework #kernel #learning #multi
A Binary Classification Framework for Two-Stage Multiple Kernel Learning (AK, ANM, KK, HDI), p. 173.
ICMLICML-2012-McDowellA #hybrid
Semi-Supervised Collective Classification via Hybrid Label Regularization (LM, DWA), p. 162.
ICMLICML-2012-MorvantKR #bound #matrix #multi
PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class Classification (EM, SK, LR), p. 158.
ICMLICML-2012-TakedaMK #robust
A Unified Robust Classification Model (AT, HM, TK), p. 71.
ICPRICPR-2012-0007B #feature model #image #kernel #multi
Multiple local kernel integrated feature selection for image classification (YS, BB), pp. 2230–2233.
ICPRICPR-2012-AliGBPNP #biology #using
Classification of biological cells using bio-inspired descriptors (WBHA, DG, MB, PP, RN, TP), pp. 3353–3357.
ICPRICPR-2012-AroraE #automation #case study #comparative #towards
Towards automated classification of fine-art painting style: A comparative study (RSA, AME), pp. 3541–3544.
ICPRICPR-2012-AryafarJS #automation #using
Automatic musical genre classification using sparsity-eager support vector machines (KA, SJ, AS), pp. 1526–1529.
ICPRICPR-2012-BaiXP #image
Classification oriented semi-supervised band selection for hyperspectral images (JB, SX, CP), pp. 1888–1891.
ICPRICPR-2012-BattiatoFGP #modelling
Aligning Bags of Shape Contexts for Blurred Shape Model based symbol classification (SB, GMF, OG, GP), pp. 1598–1601.
ICPRICPR-2012-Berrar #comparison #null #testing #visual notation
Null QQ plots: A simple graphical alternative to significance testing for the comparison of classifiers (DPB), pp. 1852–1855.
ICPRICPR-2012-BespalovQBS #image #scalability #using
Large-scale image classification using supervised spatial encoder (DB, YQ, BB, AS), pp. 581–584.
ICPRICPR-2012-BougesCBL #nearest neighbour #using
Using k-nearest neighbors to handle missing weak classifiers in a boosted cascade (PB, TC, CB, GL), pp. 1763–1766.
ICPRICPR-2012-CataldoBFM #image
Applying textural features to the classification of HEp-2 cell patterns in IIF images (SDC, AB, EF, EM), pp. 3349–3352.
ICPRICPR-2012-ChangrampadiYG #image #multi #visual notation
Multi-class ada-boost classification of object poses through visual and infrared image information fusion (MHC, YY, IYHG), pp. 2865–2868.
ICPRICPR-2012-ChenCZ #clique #representation
Object clique representation for scene classification (JC, XC, BZ), pp. 2829–2832.
ICPRICPR-2012-ChenH0N #documentation
Structured document classification by matching local salient features (SC, YH, JS, SN), pp. 653–656.
ICPRICPR-2012-ConnollyGS #correlation #on the
On the correlation between genotype and classifier diversity (JFC, EG, RS), pp. 1068–1071.
ICPRICPR-2012-CoronaTG #multi #named #web #web service
SuStorID: A multiple classifier system for the protection of web services (IC, RT, GG), pp. 2375–2378.
ICPRICPR-2012-CourtyAL #approach #image
A classwise supervised ordering approach for morphology based hyperspectral image classification (NC, EA, SL), pp. 1997–2000.
ICPRICPR-2012-DongYDWYGSM #linear
A Linear Max K-min classifier (MD, LY, WD, QW, CY, JG, LS, LM), pp. 2967–2971.
ICPRICPR-2012-DubrovinaKFSB #image #performance #robust #user interface
Efficient and robust image descriptor for GUI object classification (AD, PK, DF, SS, RB), pp. 3594–3597.
ICPRICPR-2012-DufourZWK
Classification of drusen positions in optical coherence tomography data from patients with age-related macular degeneration (PAD, SDZ, UWS, JK), pp. 2067–2070.
ICPRICPR-2012-ErsoyBPP #image #using
HEp-2 cell classification in IIF images using Shareboost (IE, FB, JP, KP), pp. 3362–3365.
ICPRICPR-2012-GhoshC #analysis #automation
Feature analysis for automatic classification of HEp-2 florescence patterns : Computer-Aided Diagnosis of Auto-immune diseases (SG, VC), pp. 174–177.
ICPRICPR-2012-GlodekSPS #markov #multi #network #using
Multi-modal Fusion based on classifiers using reject options and Markov Fusion Networks (MG, MS, GP, FS), pp. 1084–1087.
ICPRICPR-2012-GonfausGGRG #geometry #using
Edge classification using photo-geometric features (JMG, TG, AG, FXR, JG), pp. 1497–1500.
ICPRICPR-2012-GujraniyaM #modelling #performance #topic #using
Efficient classification using phrases generated by topic models (DG, MNM), pp. 2331–2334.
ICPRICPR-2012-GuoRM #representation #similarity
Similarity weighted sparse representation for classification (SG, QR, ZM), pp. 1241–1244.
ICPRICPR-2012-HanQC #adaptation #image #representation
Group sparse representation of adaptive sub-domain selection for image classification (XHH, XQ, YWC), pp. 1431–1434.
ICPRICPR-2012-JensenED #feature model
Classification of kinematic golf putt data with emphasis on feature selection (UJ, BE, FD), pp. 1735–1738.
ICPRICPR-2012-JoshiDGBP #analysis
Neural-net classification for spatio-temporal descriptor based depression analysis (JJ, AD, RG, MB, GP), pp. 2634–2638.
ICPRICPR-2012-KafaiBA #clustering #estimation #network
Cluster-Classification Bayesian Networks for head pose estimation (MK, BB, LA), pp. 2869–2872.
ICPRICPR-2012-KalkanNDL #automation
Automated classification of local patches in colon histopathology (HK, MN, RPWD, ML), pp. 61–64.
ICPRICPR-2012-KangLXP #kernel #representation
Kernel Homotopy based sparse representation for object classification (CK, SL, SX, CP), pp. 1479–1482.
ICPRICPR-2012-KimP #rating #visual notation
Attribute rating for classification of visual objects (JK, VP), pp. 1611–1614.
ICPRICPR-2012-KockelkornSGRJVRSG #interactive #simulation
Interactive classification of lung tissue in CT scans by combining prior and interactively obtained training data: A simulation study (TTJPK, CIS, JCG, RR, PAdJ, MAV, JR, CSP, BvG), pp. 105–108.
ICPRICPR-2012-KrawczykS #analysis #effectiveness #multi
Effective multiple classifier systems for breast thermogram analysis (BK, GS), pp. 3345–3348.
ICPRICPR-2012-KrijtheHL #using
Improving cross-validation based classifier selection using meta-learning (JHK, TKH, ML), pp. 2873–2876.
ICPRICPR-2012-KumarYD #documentation #learning #retrieval
Learning document structure for retrieval and classification (JK, PY, DSD), pp. 1558–1561.
ICPRICPR-2012-LiDL #image #multi
Combining multi-scale dissimilarities for image classification (YL, RPWD, ML), pp. 1639–1642.
ICPRICPR-2012-LiPMH #email #incremental #learning #using
Business email classification using incremental subspace learning (ML, YP, RM, HYH), pp. 625–628.
ICPRICPR-2012-LiuJSET #image #segmentation
Watershed merge tree classification for electron microscopy image segmentation (TL, EJ, MS, MHE, TT), pp. 133–137.
ICPRICPR-2012-LiuWXZS
Soft-signed sparse coding for ground-based cloud classification (SL, CW, BX, ZZ, YS), pp. 2214–2217.
ICPRICPR-2012-LiuXFLMK #modelling #multi #statistics
Statistical modeling and signal selection in multivariate time series pattern classification (RL, SX, CF, YwL, YLM, DSK), pp. 2853–2856.
ICPRICPR-2012-LiYLKZL #multi #using
Multiclass boosting SVM using different texture features in HEp-2 cell staining pattern classification (KL, JY, ZL, XK, RZ, WL), pp. 170–173.
ICPRICPR-2012-Lotte
A new feature and associated optimal spatial filter for EEG signal classification: Waveform Length (FL), pp. 1302–1305.
ICPRICPR-2012-LuLY #adaptation #kernel #learning
Adaptive kernel learning based on centered alignment for hierarchical classification (YL, JL, JY), pp. 569–572.
ICPRICPR-2012-LuWH #gender
Gait-based gender classification in unconstrained environments (JL, GW, TSH), pp. 3284–3287.
ICPRICPR-2012-MaoYLZ #invariant #verification
Age-invariant face verification based on Local Classifier Ensemble (XJM, YBY, NL, YZ), pp. 2408–2411.
ICPRICPR-2012-MiyamotoMSS #3d #estimation #precise #realtime
Real-time and precise 3-D hand posture estimation based on classification tree trained with variations of appearances (SM, TM, NS, YS), pp. 453–456.
ICPRICPR-2012-MoZW #learning
Enhancing cross-view object classification by feature-based transfer learning (YM, ZZ, YW), pp. 2218–2221.
ICPRICPR-2012-Noh #analysis #learning #metric #nearest neighbour
χ2 Metric learning for nearest neighbor classification and its analysis (SN), pp. 991–995.
ICPRICPR-2012-PangHYQW #analysis #learning
Theoretical analysis of learning local anchors for classification (JP, QH, BY, LQ, DW), pp. 1803–1806.
ICPRICPR-2012-PillaiFR #multi #optimisation
F-measure optimisation in multi-label classifiers (IP, GF, FR), pp. 2424–2427.
ICPRICPR-2012-RattaniMGR #approach #automation
A dual-staged classification-selection approach for automated update of biometric templates (AR, GLM, EG, FR), pp. 2972–2975.
ICPRICPR-2012-RenZMZ #image #multi #optimisation
Hyperspectral image classification based on Multiple Improved particle swarm cooperative optimization and SVM (YR, YZ, QM, LZ), pp. 2274–2277.
ICPRICPR-2012-RichterGE #image #web
Facial expression classification on web images (MR, TG, HKE), pp. 3517–3520.
ICPRICPR-2012-RingJKE #analysis #complexity #design #embedded #performance
Software-based performance and complexity analysis for the design of embedded classification systems (MR, UJ, PK, BE), pp. 2266–2269.
ICPRICPR-2012-RoyH #component #detection #documentation #image #using
Text detection on camera acquired document images using supervised classification of connected components in wavelet domain (UR, GH), pp. 270–273.
ICPRICPR-2012-San-BiagioUCCCM #approach #kernel #learning #multi
A multiple kernel learning approach to multi-modal pedestrian classification (MSB, AU, MC, MC, UC, VM), pp. 2412–2415.
ICPRICPR-2012-SantosFTRGPF #analysis #correlation #image #multi
Descriptor correlation analysis for remote sensing image multi-scale classification (JAdS, FAF, RdST, AR, PHG, SPF, AXF), pp. 3078–3081.
ICPRICPR-2012-SantosPTGPF #image #multi #using #visual notation #word
Improving texture description in remote sensing image multi-scale classification tasks by using visual words (JAdS, OABP, RdST, PHG, SPF, AXF), pp. 3090–3093.
ICPRICPR-2012-SchuldhausKJESL #using
Classification of surfaces and inclinations during outdoor running using shoe-mounted inertial sensors (DS, PK, UJ, BE, HS, ML), pp. 2258–2261.
ICPRICPR-2012-SermanetCL #network
Convolutional neural networks applied to house numbers digit classification (PS, SC, YL), pp. 3288–3291.
ICPRICPR-2012-SharmaHN #detection #incremental #learning #performance
Efficient incremental learning of boosted classifiers for object detection (PS, CH, RN), pp. 3248–3251.
ICPRICPR-2012-SjobergKIL #concept #detection #linear #realtime #scalability #visual notation
Real-time large-scale visual concept detection with linear classifiers (MS, MK, SI, JL), pp. 421–424.
ICPRICPR-2012-StrandmarkUK
HEp-2 staining pattern classification (PS, JU, FK), pp. 33–36.
ICPRICPR-2012-SuYLW #bound #editing #using
Local color editing using color classification and boundary inpainting (ZS, XY, XL, DW), pp. 3196–3199.
ICPRICPR-2012-ThakoorB #video
Structural signatures for passenger vehicle classification in video (NT, BB), pp. 926–929.
ICPRICPR-2012-ThibaultA #performance #statistics
Efficient statistical/morphological cell texture characterization and classification (GT, JA), pp. 2440–2443.
ICPRICPR-2012-TimofteG #collaboration #image #representation
Weighted collaborative representation and classification of images (RT, LJVG), pp. 1606–1610.
ICPRICPR-2012-TuiaMVFR #image
Discovering relevant spatial filterbanks for VHR image classification (DT, MDM, MV, RF, AR), pp. 3212–3215.
ICPRICPR-2012-TuS #adaptation #learning
Dynamical ensemble learning with model-friendly classifiers for domain adaptation (WT, SS), pp. 1181–1184.
ICPRICPR-2012-TyagiKFSR #identification
Fusing biographical and biometric classifiers for improved person identification (VT, HPK, TAF, LVS, NKR), pp. 2351–2354.
ICPRICPR-2012-Utasi #dataset
Weighted conditional mutual information based boosting for classification of imbalanced datasets (ÁU), pp. 2711–2714.
ICPRICPR-2012-ValevY #clustering #graph #using
Classification using graph partitioning (VV, NY), pp. 1261–1264.
ICPRICPR-2012-VieuxD #clustering #documentation #image
Hierarchical clustering model for pixel-based classification of document images (RV, JPD), pp. 290–293.
ICPRICPR-2012-WangHWZ #gender #using
Facial image-based gender classification using Local Circular Patterns (CW, DH, YW, GZ), pp. 2432–2435.
ICPRICPR-2012-WangWZBL #image
Adjacent coding for image classification (YW, XW, SZ, XB, WL), pp. 1459–1462.
ICPRICPR-2012-WangXY #image #re-engineering
Sparse residue for occluded face image reconstruction and classification (JW, YX, JY), pp. 1707–1710.
ICPRICPR-2012-WuHWT #encoding #image
Group encoding of local features in image classification (ZW, YH, LW, TT), pp. 1505–1508.
ICPRICPR-2012-WuW #dependence
Term relevance dependency model for text classification (MSW, HMW), pp. 1064–1067.
ICPRICPR-2012-XueCH #constraints #kernel
Discriminative indefinite kernel classifier from pairwise constraints and unlabeled data (HX, SC, JH), pp. 497–500.
ICPRICPR-2012-XuLCYTWCTW #image #locality #performance
Efficient optic cup localization based on superpixel classification for glaucoma diagnosis in digital fundus images (YX, JL, JC, FY, NMT, DWKW, CYC, YCT, TYW), pp. 49–52.
ICPRICPR-2012-YamasakiC #recognition #refinement
Confidence-assisted classification result refinement for object recognition featuring TopN-Exemplar-SVM (TY, TC), pp. 1783–1786.
ICPRICPR-2012-YangGAZW #clustering #query
Iterative clustering and support vectors-based high-confidence query selection for motor imagery EEG signals classification (HY, CG, KKA, HZ, CW), pp. 2169–2172.
ICPRICPR-2012-YanRLS #learning #multi
Active transfer learning for multi-view head-pose classification (YY, SR, OL, NS), pp. 1168–1171.
ICPRICPR-2012-YeKC #multi
Combining general multi-class and specific two-class classifiers for improved customized ECG heartbeat classification (CY, BVKVK, MTC), pp. 2428–2431.
ICPRICPR-2012-YiP #graph
Sparse Granger causality graphs for human action classification (SY, VP), pp. 3374–3377.
ICPRICPR-2012-YlioinasHP #using
Age Classification in Unconstrained Conditions Using LBP Variants (JY, AH, MP), pp. 1257–1260.
ICPRICPR-2012-ZhangHR #gender #learning
Hypergraph based semi-supervised learning for gender classification (ZZ, ERH, PR), pp. 1747–1750.
ICPRICPR-2012-ZhangLGZ #feature model
An improved EEMD model for feature extraction and classification of gunshot in public places (ZZ, WL, WG, JZ), pp. 1517–1520.
ICPRICPR-2012-ZhangSTW #image
Iris image classification based on color information (HZ, ZS, TT, JW), pp. 3427–3430.
ICPRICPR-2012-ZhuoCQYX #algorithm #image #learning #using
Image classification using HTM cortical learning algorithms (WZ, ZC, YQ, ZY, YX), pp. 2452–2455.
ICPRICPR-2012-ZnaidiaSBHP #image #multi
Bag-of-multimedia-words for image classification (AZ, AS, HLB, CH, NP), pp. 1509–1512.
KDDKDD-2012-JanWLL
A simple methodology for soft cost-sensitive classification (TKJ, DWW, CHL, HTL), pp. 141–149.
KDDKDD-2012-LiJPS #learning #multi
Multi-domain active learning for text classification (LL, XJ, SJP, JTS), pp. 1086–1094.
KDDKDD-2012-LinesDHB
A shapelet transform for time series classification (JL, LMD, JH, AB), pp. 289–297.
KDDKDD-2012-LouCG #modelling
Intelligible models for classification and regression (YL, RC, JG), pp. 150–158.
KDDKDD-2012-YuDRZY #multi #predict
Transductive multi-label ensemble classification for protein function prediction (GXY, CD, HR, GZ, ZY), pp. 1077–1085.
KDIRKDIR-2012-HavaSK #documentation #network #semantics
Contextual Latent Semantic Networks used for Document Classification (OH, MS, PK), pp. 425–430.
KDIRKDIR-2012-LemnaruSVP #documentation #taxonomy
A System for Historical Documents Transcription based on Hierarchical Classification and Dictionary Matching (CL, ASN, MAV, RP), pp. 353–357.
KDIRKDIR-2012-LemnaruTCP #case study #detection #hybrid #network #problem
A Hybrid Solution for Imbalanced Classification Problems — Case Study on Network Intrusion Detection (CL, ATV, AC, RP), pp. 348–352.
KDIRKDIR-2012-Vanetik #dataset
Classification of Datasets with Frequent Itemsets is Wild (NV), pp. 386–389.
KEODKEOD-2012-AlirezaieL #low level #ontology
Ontology Alignment for Classification of Low Level Sensor Data (MA, AL), pp. 89–97.
MLDMMLDM-2012-Ba-KaraitSS #hybrid #optimisation #using
EEG Signals Classification Using a Hybrid Method Based on Negative Selection and Particle Swarm Optimization (NOSBK, SMS, RS), pp. 427–438.
MLDMMLDM-2012-CarvalhoPS #image #using
Classification of Breast Tissues in Mammographic Images in Mass and Non-mass Using McIntosh’s Diversity Index and SVM (PMdSC, ACdP, ACS), pp. 482–494.
MLDMMLDM-2012-CeciAVMPG #paradigm #relational
Transductive Relational Classification in the Co-training Paradigm (MC, AA, HLV, DM, EP, HG), pp. 11–25.
MLDMMLDM-2012-DiezC #approach #multi #predict
A Multiclassifier Approach for Drill Wear Prediction (AD, AC), pp. 617–630.
MLDMMLDM-2012-ForczmanskiF #distance #representation
Classification of Elementary Stamp Shapes by Means of Reduced Point Distance Histogram Representation (PF, DF), pp. 603–616.
MLDMMLDM-2012-Garcia-ConstantinoCNRS #approach #automation #summary
A Semi-Automated Approach to Building Text Summarisation Classifiers (MGC, FC, PJN, AR, CS), pp. 495–509.
MLDMMLDM-2012-LeiteBV #algorithm #testing
Selecting Classification Algorithms with Active Testing (RL, PB, JV), pp. 117–131.
MLDMMLDM-2012-Moreira-MatiasMGB #categorisation #matrix #using
Text Categorization Using an Ensemble Classifier Based on a Mean Co-association Matrix (LMM, JMM, JG, PB), pp. 525–539.
MLDMMLDM-2012-NascimentoPS #image #using
Lung Nodules Classification in CT Images Using Shannon and Simpson Diversity Indices and SVM (LBN, ACdP, ACS), pp. 454–466.
MLDMMLDM-2012-TabatabaeiAKK #internet #machine learning
Machine Learning-Based Classification of Encrypted Internet Traffic (TST, MA, FK, MK), pp. 578–592.
MLDMMLDM-2012-Thombre #network
Comparing Logistic Regression, Neural Networks, C5.0 and M5′ Classification Techniques (AT), pp. 132–140.
MLDMMLDM-2012-YangW #modelling
Generalized Nonlinear Classification Model Based on Cross-Oriented Choquet Integral (RY, ZW), pp. 26–39.
SEKESEKE-2012-HaoWZ #empirical #machine learning
An Empirical Study of Execution-Data Classification Based on Machine Learning (DH, XW, LZ), pp. 283–288.
SEKESEKE-2012-NoorianBD #non-functional #product line #taxonomy
Non-functional Properties in Software Product Lines: A Taxonomy for Classification (MN, EB, WD), pp. 663–667.
SIGIRSIGIR-2012-BerardiES #automation #ranking
A utility-theoretic ranking method for semi-automated text classification (GB, AE, FS), pp. 961–970.
SIGIRSIGIR-2012-HuO #dataset #using
Genre classification for million song dataset using confidence-based classifiers combination (YH, MO), pp. 1083–1084.
SIGIRSIGIR-2012-Ko #case study #using
A study of term weighting schemes using class information for text classification (YK), pp. 1029–1030.
SIGIRSIGIR-2012-LipkaSA #clustering #information retrieval #problem
Cluster-based one-class ensemble for classification problems in information retrieval (NL, BS, MA), pp. 1041–1042.
SIGIRSIGIR-2012-NishidaHF #detection #probability #twitter #word
Improving tweet stream classification by detecting changes in word probability (KN, TH, KF), pp. 971–980.
SIGIRSIGIR-2012-NunzioS #data analysis #naive bayes #visual notation
A visual tool for bayesian data analysis: the impact of smoothing on naive bayes text classifiers (GMDN, AS), p. 1002.
SIGIRSIGIR-2012-Sun #using #word
Short text classification using very few words (AS), pp. 1145–1146.
SIGIRSIGIR-2012-ZerrSHD #image #privacy
Privacy-aware image classification and search (SZ, SS, JSH, ED), pp. 35–44.
SIGIRSIGIR-2012-ZhangFQDSY #online
Emotion tagging for comments of online news by meta classification with heterogeneous information sources (YZ, YF, XQ, LD, LS, XY), pp. 1059–1060.
AdaEuropeAdaEurope-2012-PoonCT
Choices, Choices: Comparing between CHOC’LATE and the Classification-Tree Methodology (PLP, TYC, THT), pp. 162–176.
PADLPADL-2012-Coleman #distributed #policy #specification
Distributed Policy Specification and Interpretation with Classified Advertisements (NC), pp. 198–211.
ICSEICSE-2012-BacchelliSDL #development #email
Content classification of development emails (AB, TDS, MD, ML), pp. 375–385.
SACSAC-2012-CerriBC #algorithm #multi #search-based
A genetic algorithm for Hierarchical Multi-Label Classification (RC, RCB, ACPLFdC), pp. 250–255.
SACSAC-2012-EgginkAB #case study
A pilot study for mood-based classification of TV programmes (JE, PA, DB), pp. 918–922.
SACSAC-2012-NathML #fault #on the #testing
On the improvement of a fault classification scheme with implications for white-box testing (SKN, RM, MFL), pp. 1123–1130.
SACSAC-2012-OongI #fuzzy #learning #multi #performance #testing
Multilayer Fuzzy ARTMAP: fast learning and fast testing for pattern classification (THO, NAMI), pp. 27–32.
SACSAC-2012-WickerPK #composition #matrix #multi #using
Multi-label classification using boolean matrix decomposition (JW, BP, SK), pp. 179–186.
DACDAC-2012-GuoYSCZ #distance #metric
Improved tangent space based distance metric for accurate lithographic hotspot classification (JG, FY, SS, CC, XZ), pp. 1173–1178.
DATEDATE-2012-ParkKSNI
An FPGA-based accelerator for cortical object classification (MSP, SK, JS, VN, MJI), pp. 691–696.
FASEFASE-2012-MahouachiKG #design #detection #fault
A New Design Defects Classification: Marrying Detection and Correction (RM, MK, KG), pp. 455–470.
FASEFASE-2012-MauczkaHSSBG #automation #commit #maintenance #taxonomy #validation
Tracing Your Maintenance Work — A Cross-Project Validation of an Automated Classification Dictionary for Commit Messages (AM, MH, CS, WS, MB, TG), pp. 301–315.
CAVCAV-2012-SharmaNA
Interpolants as Classifiers (RS, AVN, AA), pp. 71–87.
ICSTICST-2012-KruseW #generative #sequence #testing
Test Sequence Generation from Classification Trees (PMK, JW), pp. 539–548.
ICSTICST-2012-ShakyaXLLKK #combinator #testing #using
Isolating Failure-Inducing Combinations in Combinatorial Testing Using Test Augmentation and Classification (KS, TX, NL, YL, RK, DRK), pp. 620–623.
ICSTICST-2012-SprenkleCP #modelling #statistics #web
Leveraging User-Privilege Classification to Customize Usage-based Statistical Models of Web Applications (SS, CC, LLP), pp. 161–170.
DRRDRR-2011-XieA
Boosting based text and non-text region classification (BX, GA), pp. 1–10.
HTHT-2011-ZubiagaKS #social
Tags vs shelves: from social tagging to social classification (AZ, CK, MS), pp. 93–102.
ICDARICDAR-2011-CiresanMGS #network
Convolutional Neural Network Committees for Handwritten Character Classification (DCC, UM, LMG, JS), pp. 1135–1139.
ICDARICDAR-2011-DiemKS #analysis #documentation #layout
Text Classification and Document Layout Analysis of Paper Fragments (MD, FK, RS), pp. 854–858.
ICDARICDAR-2011-ImpedovoP #multi
Updating Knowledge in Feedback-Based Multi-classifier Systems (DI, GP), pp. 227–231.
ICDARICDAR-2011-KokawaBOWK #analysis #automation #fault
An Impact of OCR Errors on Automated Classification of OCR Japanese Texts with Parts-of-Speech Analysis (AK, LSPB, WO, TW, FK), pp. 543–547.
ICDARICDAR-2011-KumarPD #documentation #image #learning #multi #using
Document Image Classification and Labeling Using Multiple Instance Learning (JK, JP, DSD), pp. 1059–1063.
ICDARICDAR-2011-LuoOWK #automation #case study
A Study on Automatic Chinese Text Classification (XL, WO, TW, FK), pp. 920–924.
ICDARICDAR-2011-NguyenCO #approach
Bags of Strokes Based Approach for Classification and Indexing of Drop Caps (TTHN, MC, JMO), pp. 349–353.
ICDARICDAR-2011-PackerTK #recognition
alpha-Shape Based Classification with Applications to Optical Character Recognition (EP, AT, VK), pp. 344–348.
ICDARICDAR-2011-ShivakumaraPLT #recognition #video
Video Character Recognition through Hierarchical Classification (PS, TQP, SL, CLT), pp. 131–135.
ICDARICDAR-2011-ZhuN11a #online #recognition #scalability
A Coarse Classifier Construction Method from a Large Number of Basic Recognizers for On-line Recognition of Handwritten Japanese Characters (BZ, MN), pp. 1090–1094.
JCDLJCDL-2011-KawaseH #folksonomy #using
Classification of user interest patterns using a virtual folksonomy (RK, EH), pp. 105–108.
TPDLTPDL-2011-EckertP #library #scalability
An Application to Support Reclassification of Large Libraries (KE, MP), pp. 461–464.
VLDBVLDB-2011-KocR #incremental #maintenance #using
Incrementally maintaining classification using an RDBMS (MLK, CR), pp. 302–313.
SCAMSCAM-J-2009-HollandD11 #information management #quality #tool support
Classification and selection of tools for quality knowledge management (SH, RD), pp. 393–409.
LATALATA-2011-AnselmoGM #string
Classification of String Languages via Tiling Recognizable Picture Languages (MA, DG, MM), pp. 105–116.
CoGVS-Games-2011-Anderson #game studies
A Classification of Scripting Systems for Entertainment and Serious Computer Games (EFA), pp. 47–54.
HCIDHM-2011-TangoMAP #automation #behaviour
Automation Effects on Driver’s Behaviour When Integrating a PADAS and a Distraction Classifier (FT, LM, RA, OP), pp. 503–512.
HCIDUXU-v2-2011-MasipOG #component #evaluation #heuristic #interactive
Classification of Interactive System Components Enables Planning Heuristic Evaluation Easier (LM, MO, TG), pp. 478–486.
HCIHCI-MIIE-2011-KarthikP #adaptation #approach #email #machine learning
Adaptive Machine Learning Approach for Emotional Email Classification (KK, RP), pp. 552–558.
HCIHCI-MIIE-2011-WalterSSGHSBLTS #behaviour #multimodal
Multimodal Emotion Classification in Naturalistic User Behavior (SW, SS, MS, MG, DH, MS, RB, KL, HCT, FS), pp. 603–611.
HCIHIMI-v2-2011-MozaffariM #mining #visual notation
A Classification Scheme for Characterizing Visual Mining (EM, SPM), pp. 46–54.
ICEISICEIS-J-2011-LemnaruP #problem
Imbalanced Classification Problems: Systematic Study, Issues and Best Practices (CL, RP), pp. 35–50.
ICEISICEIS-v1-2011-ChagheriCRD #documentation
Document Classification — Combining Structure and Content (SC, SC, CR, CD), pp. 95–100.
ICEISICEIS-v1-2011-PotoleaL #performance
A Comprehensive Study of the Effect of Class Imbalance on the Performance of Classifiers (RP, CL), pp. 14–21.
CIKMCIKM-2011-AnderkaSL #detection #problem #quality
Detection of text quality flaws as a one-class classification problem (MA, BS, NL), pp. 2313–2316.
CIKMCIKM-2011-BespalovBQS #analysis #n-gram #sentiment
Sentiment classification based on supervised latent n-gram analysis (DB, BB, YQ, AS), pp. 375–382.
CIKMCIKM-2011-BianC #query #taxonomy
A taxonomy of local search: semi-supervised query classification driven by information needs (JB, YC), pp. 2425–2428.
CIKMCIKM-2011-CaiZLZ #scalability #semantics #wiki
Large-scale question classification in cQA by leveraging Wikipedia semantic knowledge (LC, GZ, KL, JZ), pp. 1321–1330.
CIKMCIKM-2011-ChenSNC #adaptation #query #self
Improving context-aware query classification via adaptive self-training (MC, JTS, XN, YC), pp. 115–124.
CIKMCIKM-2011-GaoL #adaptation #analysis #probability #sentiment #using
A cross-domain adaptation method for sentiment classification using probabilistic latent analysis (SG, HL), pp. 1047–1052.
CIKMCIKM-2011-Garza #matrix
Structured data classification by means of matrix factorization (PG), pp. 2165–2168.
CIKMCIKM-2011-JacobDG #corpus #multi #social #using
Classification and annotation in social corpora using multiple relations (YJ, LD, PG), pp. 1215–1220.
CIKMCIKM-2011-LinTC #independence #sentiment #using #word
Language-independent sentiment classification using three common words (ZL, ST, XC), pp. 1041–1046.
CIKMCIKM-2011-LiuLZD #network #sentiment
Sentiment classification via l2-norm deep belief network (TL, ML, SZ, XD), pp. 2489–2492.
CIKMCIKM-2011-LiuNSC #comprehension #query #transaction
Unsupervised transactional query classification based on webpage form understanding (YL, XN, JTS, ZC), pp. 57–66.
CIKMCIKM-2011-LiZWLW #sentiment
Imbalanced sentiment classification (SL, GZ, ZW, SYML, RW), pp. 2469–2472.
CIKMCIKM-2011-LuLYYH #modelling #parametricity
Coarse-to-fine classification via parametric and nonparametric models for computer-aided diagnosis (ML, LL, XY, SY, HH), pp. 2509–2512.
CIKMCIKM-2011-QiD #evolution
Hierarchy evolution for improved classification (XQ, BDD), pp. 2193–2196.
CIKMCIKM-2011-SelvarajBSS #dataset
Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset (SKS, BB, SS, SKS), pp. 653–662.
CIKMCIKM-2011-TomasevRMI #approach #nearest neighbour #probability
A probabilistic approach to nearest-neighbor classification: naive hubness bayesian kNN (NT, MR, DM, MI), pp. 2173–2176.
CIKMCIKM-2011-VinzamuriK #convergence #design #using
Designing an ensemble classifier over subspace classifiers using iterative convergence routine (BV, KK), pp. 693–698.
CIKMCIKM-2011-WangWLZZ #analysis #approach #graph #hashtag #sentiment #topic #twitter
Topic sentiment analysis in twitter: a graph-based hashtag sentiment classification approach (XW, FW, XL, MZ, MZ), pp. 1031–1040.
CIKMCIKM-2011-WangZLBW #multi #random #using
Using random walks for multi-label classification (CW, WZ, ZL, YB, JW), pp. 2197–2200.
CIKMCIKM-2011-YooYC #email #modelling #personalisation
Modeling personalized email prioritization: classification-based and regression-based approaches (SY, YY, JGC), pp. 729–738.
ECIRECIR-2011-Dulac-ArnoldDG #approach
Text Classification: A Sequential Reading Approach (GDA, LD, PG), pp. 411–423.
ECIRECIR-2011-He #sentiment
Latent Sentiment Model for Weakly-Supervised Cross-Lingual Sentiment Classification (YH), pp. 214–225.
ECIRECIR-2011-KinsellaPB #metadata #social #social media #topic #using
Topic Classification in Social Media Using Metadata from Hyperlinked Objects (SK, AP, JGB), pp. 201–206.
ECIRECIR-2011-OhCM #modelling #scalability #taxonomy #using
Text Classification for a Large-Scale Taxonomy Using Dynamically Mixed Local and Global Models for a Node (HSO, YC, SHM), pp. 7–18.
ICMLICML-2011-BiK #multi
MultiLabel Classification on Tree- and DAG-Structured Hierarchies (WB, JTK), pp. 17–24.
ICMLICML-2011-CrammerG #adaptation #feedback #multi #using
Multiclass Classification with Bandit Feedback using Adaptive Regularization (KC, CG), pp. 273–280.
ICMLICML-2011-FlachHR #performance
A Coherent Interpretation of AUC as a Measure of Aggregated Classification Performance (PAF, JHO, CFR), pp. 657–664.
ICMLICML-2011-GabillonLGS #policy
Classification-based Policy Iteration with a Critic (VG, AL, MG, BS), pp. 1049–1056.
ICMLICML-2011-GlorotBB #adaptation #approach #learning #scalability #sentiment
Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach (XG, AB, YB), pp. 513–520.
ICMLICML-2011-Hernandez-OralloFR #cost analysis #performance #visualisation
Brier Curves: a New Cost-Based Visualisation of Classifier Performance (JHO, PAF, CFR), pp. 585–592.
ICMLICML-2011-KuwadekarN #learning #modelling #relational
Relational Active Learning for Joint Collective Classification Models (AK, JN), pp. 385–392.
ICMLICML-2011-Scott #bound
Surrogate losses and regret bounds for cost-sensitive classification with example-dependent costs (CS), pp. 153–160.
ICMLICML-2011-SuSM #multi #naive bayes #scalability #using
Large Scale Text Classification using Semisupervised Multinomial Naive Bayes (JS, JSS, SM), pp. 97–104.
ICMLICML-2011-XiaoZW #orthogonal
Hierarchical Classification via Orthogonal Transfer (LX, DZ, MW), pp. 801–808.
KDDKDD-2011-BekkermanG #documentation
High-precision phrase-based document classification on a modern scale (RB, MG), pp. 231–239.
KDDKDD-2011-CerratoJG #generative
Classification of proxy labeled examples for marketing segment generation (DC, RJ, AG), pp. 343–350.
KDDKDD-2011-IfrimW #biology #bound #coordination #predict #sequence
Bounded coordinate-descent for biological sequence classification in high dimensional predictor space (GI, CW), pp. 708–716.
KDDKDD-2011-JiHD #network
Ranking-based classification of heterogeneous information networks (MJ, JH, MD), pp. 1298–1306.
KDDKDD-2011-KongFY #graph
Dual active feature and sample selection for graph classification (XK, WF, PSY), pp. 654–662.
KDDKDD-2011-MooreYZRL #learning #network
Active learning for node classification in assortative and disassortative networks (CM, XY, YZ, JBR, TL), pp. 841–849.
KDDKDD-2011-MueenKY #named
Logical-shapelets: an expressive primitive for time series classification (AM, EJK, NEY), pp. 1154–1162.
KDDKDD-2011-PennacchiottiP #twitter
Democrats, republicans and starbucks afficionados: user classification in twitter (MP, AMP), pp. 430–438.
KDDKDD-2011-PereiraB #functional #using
Classification of functional magnetic resonance imaging data using informative pattern features (FP, MB), pp. 940–946.
KDDKDD-2011-SimonKL #statistics
A simple statistical model and association rule filtering for classification (GJS, VK, PWL), pp. 823–831.
KDDKDD-2011-WangDCV #adaptation #multi #scalability
Trading representability for scalability: adaptive multi-hyperplane machine for nonlinear classification (ZW, ND, KC, SV), pp. 24–32.
KDDKDD-2011-WilkinsonAN #named #random
CHIRP: a new classifier based on composite hypercubes on iterated random projections (LW, AA, DTN), pp. 6–14.
KDIRKDIR-2011-AliDKB #image
Bio-inspired Bags-of-features for Image Classification (WBHA, ED, PK, MB), pp. 277–281.
KDIRKDIR-2011-ArmengolP #case study #information management #lazy evaluation #learning
Combining Two Lazy Learning Methods for Classification and Knowledge Discovery — A Case Study for Malignant Melanoma Diagnosis (EA, SP), pp. 200–207.
KDIRKDIR-2011-ClariziaCSGN11a #novel #set
A Novel Supervised Text Classifier from a Small Training Set (FC, FC, MDS, LG, PN), pp. 545–553.
KDIRKDIR-2011-CostaRO #approach #transaction #xml
A Transactional Approach to Associative XML Classification by Content and Structure (GC, RO, ER), pp. 104–113.
KDIRKDIR-2011-NguyenLT #image #multi
Cascade of Multi-level Multi-instance Classifiers for Image Annotation (CTN, HVL, TT), pp. 14–23.
KDIRKDIR-2011-PrachuabsupakijS #multi #set #using
Multi-class Data Classification for Imbalanced Data Set using Combined Sampling Approaches (WP, NS), pp. 166–171.
KDIRKDIR-2011-ShaikhSW #multi
Classification of Dialogue Acts in Urdu Multi-party Discourse (SS, TS, NW), pp. 406–412.
KEODKEOD-2011-FukumotoS #clustering #graph #semantics #word
Semantic Classification of Unknown Words based on Graph-based Semi-supervised Clustering (FF, YS), pp. 37–46.
KEODKEOD-2011-SuzukiF #documentation #multi #using
Multi-labeled Patent Document Classification using Technical Term Thesaurus (YS, FF), pp. 425–428.
MLDMMLDM-2011-CataltepeSBE #using
Collective Classification Using Heterogeneous Classifiers (, AS, KB, AE), pp. 155–169.
MLDMMLDM-2011-Garcia-ConstantinoCNRST #generative #summary #using
An Investigation Concerning the Generation of Text Summarisation Classifiers Using Secondary Data (MGC, FC, PJN, AR, CS, AT), pp. 387–398.
MLDMMLDM-2011-GunesCO #algorithm #named #novel #relational #search-based #using
GA-TVRC: A Novel Relational Time Varying Classifier to Extract Temporal Information Using Genetic Algorithms (IG, , SGÖ), pp. 568–583.
MLDMMLDM-2011-JoutsijokiJ #image
Comparing the One-vs-One and One-vs-All Methods in Benthic Macroinvertebrate Image Classification (HJ, MJ), pp. 399–413.
MLDMMLDM-2011-LiTM #hybrid #named #performance
ACE-Cost: Acquisition Cost Efficient Classifier by Hybrid Decision Tree with Local SVM Leaves (LL, UT, NDM), pp. 60–74.
MLDMMLDM-2011-LungaE #nearest neighbour
Spherical Nearest Neighbor Classification: Application to Hyperspectral Data (DL, OKE), pp. 170–184.
MLDMMLDM-2011-SanchezGM #reduction #tool support
Exploring Synergetic Effects of Dimensionality Reduction and Resampling Tools on Hyperspectral Imagery Data Classification (JSS, VG, RAM), pp. 511–523.
MLDMMLDM-2011-TomasevRMI #fuzzy #metric #nearest neighbour
Hubness-Based Fuzzy Measures for High-Dimensional k-Nearest Neighbor Classification (NT, MR, DM, MI), pp. 16–30.
MLDMMLDM-2011-YokotaY #estimation
Quadratically Constrained Maximum a Posteriori Estimation for Binary Classifier (TY, YY), pp. 1–15.
SEKESEKE-2011-LiJ #ontology
An Ontology based Method for Building Understandable Hierarchical Classification Structure for Software Assets Browsing (GL, ZJ), pp. 521–526.
SEKESEKE-2011-LiuZH11a #empirical #non-functional #requirements
An Empirical Study on Classification of Non-Functional Requirements (SL, RZ, XH), pp. 444–449.
SEKESEKE-2011-NoorianBD #framework #machine learning #testing #towards
Machine Learning-based Software Testing: Towards a Classification Framework (MN, EB, WD), pp. 225–229.
SIGIRSIGIR-2011-JinY #feature model #image #multi
Integrating hierarchical feature selection and classifier training for multi-label image annotation (CJ, CY), pp. 515–524.
SIGIRSIGIR-2011-KimKWHK #approach #mining
Authorship classification: a discriminative syntactic tree mining approach (SK, HK, TW, JH, HDK), pp. 455–464.
SIGIRSIGIR-2011-Martinez-Alvarez #information retrieval #integration #modelling
Descriptive modelling of text classification and its integration with other IR tasks (MMA), pp. 1317–1318.
SIGIRSIGIR-2011-SandenZ #multi #music
Enhancing multi-label music genre classification through ensemble techniques (CS, JZZ), pp. 705–714.
SIGIRSIGIR-2011-SunWY #effectiveness #towards
Towards effective short text deep classification (XS, HW, YY), pp. 1143–1144.
SIGIRSIGIR-2011-WangHND #information management #matrix #using #web
Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization (HW, HH, FN, CHQD), pp. 933–942.
ASEASE-2011-HuangNPGBT #automation #fault #generative #named #orthogonal
AutoODC: Automated generation of Orthogonal Defect Classifications (LH, VN, IP, RG, XB, JT), pp. 412–415.
ICSEICSE-2011-Kidwell #fault #research
A decision support system for the classification of software coding faults: a research abstract (BK), pp. 1158–1160.
SACSAC-2011-EcharteACVL #folksonomy
A method for the classification of folksonomy resources (FE, JJA, AC, JEV, AL), pp. 1675–1680.
SACSAC-2011-LanLSH #algorithm #analysis #case study #comparative #image
A comparative study and analysis on K-view based algorithms for image texture classification (YL, HL, ES, CCH), pp. 859–860.
SACSAC-2011-LiuSGF #performance
Improving matching performance of DPI traffic classifier (TL, YS, LG, BF), pp. 514–519.
SACSAC-2011-OsborneGCAZ
Machine classification of melanoma and nevi from skin lesions (JDO, SG, WbC, AA, CZ), pp. 100–105.
SACSAC-2011-WangZG #identification #network
Traffic classification beyond application level: identifying content types from network traces (YW, ZZ, LG), pp. 540–541.
CASECASE-2011-NazeemR #concurrent #design #policy #resource management
Designing maximally permissive deadlock avoidance policies for sequential resource allocation systems through classification theory (AN, SAR), pp. 405–412.
DACDAC-2011-WangXAP #learning #policy #power management #using
Deriving a near-optimal power management policy using model-free reinforcement learning and Bayesian classification (YW, QX, ACA, MP), pp. 41–46.
DATEDATE-2011-KangD #gpu #metaprogramming #scalability
Scalable packet classification via GPU metaprogramming (KK, YSD), pp. 871–874.
ECSAECSA-2010-EklundA #architecture
A Classification of Value for Software Architecture Decisions (UE, TA), pp. 368–375.
DocEngDocEng-2010-SorioBDM
Open world classification of printed invoices (ES, AB, GD, EM), pp. 187–190.
DRRDRR-2010-AwalMV #hybrid #recognition
A hybrid classifier for handwritten mathematical expression recognition (AMA, HM, CVG), pp. 1–10.
DRRDRR-2010-KatsuyamaMHOK
A new pre-classification method based on associative matching method (YK, AM, YH, SO, NK), pp. 1–10.
DRRDRR-2010-KimLT #naive bayes #online
Naïve Bayes and SVM classifiers for classifying databank accession number sentences from online biomedical articles (JK, DXL, GRT), pp. 1–10.
DRRDRR-2010-YinBA #documentation #optimisation
Time and space optimization of document content classifiers (DY, HSB, CA), pp. 1–10.
TPDLECDL-2010-AutayeuGA #lightweight #ontology #parsing
Lightweight Parsing of Classifications into Lightweight Ontologies (AA, FG, PA), pp. 327–339.
TPDLECDL-2010-Wartena #automation #social
Automatic Classification of Social Tags (CW), pp. 176–183.
HTHT-2010-LexJG #online
Objectivity classification in online media (EL, AJ, MG), pp. 293–294.
JCDLJCDL-2010-HuD #library #music
Improving mood classification in music digital libraries by combining lyrics and audio (XH, JSD), pp. 159–168.
SIGMODSIGMOD-2010-JinYW #graph #named #using
GAIA: graph classification using evolutionary computation (NJ, CY, WW), pp. 879–890.
ICPCICPC-2010-Taherkhani #algorithm #sorting
Recognizing Sorting Algorithms with the C4.5 Decision Tree Classifier (AT), pp. 72–75.
LATALATA-2010-CabessaV #first-order #network
A Hierarchical Classification of First-Order Recurrent Neural Networks (JC, AEPV), pp. 142–153.
CHICHI-2010-KapoorLTH #interactive #optimisation
Interactive optimization for steering machine classification (AK, BL, DST, EH), pp. 1343–1352.
ICEISICEIS-AIDSS-2010-KrohaN #predict #roadmap
Classification of Market News and Prediction of Market Trends (PK, RN), pp. 187–192.
ICEISICEIS-AIDSS-2010-SahaPMB #clustering #difference #image #using
Improvement of Differential Crisp Clustering using ANN Classifier for Unsupervised Pixel Classification of Satellite Image (IS, DP, UM, SB), pp. 21–29.
ICEISICEIS-AIDSS-2010-WatanabeRTT #statistics
Statistical Associative Classification of Mammograms — The SACMiner Method (CYVW, MXR, CTJ, AJMT), pp. 121–128.
ICEISICEIS-J-2010-WatanabeRTT10a #image #named #statistics
SACMiner: A New Classification Method Based on Statistical Association Rules to Mine Medical Images (CYVW, MXR, CTJ, AJMT), pp. 249–263.
CIKMCIKM-2010-BatalH #predict #using
Constructing classification features using minimal predictive patterns (IB, MH), pp. 869–878.
CIKMCIKM-2010-BennettC #online
Online stratified sampling: evaluating classifiers at web-scale (PNB, VRC), pp. 1581–1584.
CIKMCIKM-2010-ChaturvediFSM #scalability
Estimating accuracy for text classification tasks on large unlabeled data (SC, TAF, LVS, MKM), pp. 889–898.
CIKMCIKM-2010-EickhoffSV #web
Web page classification on child suitability (CE, PS, APdV), pp. 1425–1428.
CIKMCIKM-2010-FiranGNP #image #order #social
Bringing order to your photos: event-driven classification of flickr images based on social knowledge (CSF, MG, WN, RP), pp. 189–198.
CIKMCIKM-2010-FujinoUN #learning #robust
A robust semi-supervised classification method for transfer learning (AF, NU, MN), pp. 379–388.
CIKMCIKM-2010-GuanXZGY #analysis #documentation #performance #reduction
Fast dimension reduction for document classification based on imprecise spectrum analysis (HG, BX, JZ, MG, TY), pp. 1753–1756.
CIKMCIKM-2010-He #learning #sentiment
Learning sentiment classification model from labeled features (YH), pp. 1685–1688.
CIKMCIKM-2010-JensenS
Exploiting sequential relationships for familial classification (LSJ, JGS), pp. 1901–1904.
CIKMCIKM-2010-LinC #multi
Mr.KNN: soft relevance for multi-label classification (XL, XwC), pp. 349–358.
CIKMCIKM-2010-LiSZJZ #documentation #named
TC-DCA: a system for text classification based on document’s content allocation (WL, LS, ZZ, XJ, WZ), pp. 1937–1938.
CIKMCIKM-2010-LiuXCY #feature model #multi
Orientation distance-based discriminative feature extraction for multi-class classification (BL, YX, LC, PSY), pp. 909–918.
CIKMCIKM-2010-Nitta #documentation #scalability #taxonomy #web
Improving taxonomies for large-scale hierarchical classifiers of web documents (KN), pp. 1649–1652.
CIKMCIKM-2010-SonPS #estimation #learning #naive bayes
Learning naïve bayes transfer classifier throughclass-wise test distribution estimation (JWS, SBP, HJS), pp. 1729–1732.
CIKMCIKM-2010-ZhuangLSHXSX #collaboration #mining #multi
Collaborative Dual-PLSA: mining distinction and commonality across multiple domains for text classification (FZ, PL, ZS, QH, YX, ZS, HX), pp. 359–368.
CIKMCIKM-2010-ZhuZGX #incremental #learning
Transfer incremental learning for pattern classification (ZZ, XZ, YFG, XX), pp. 1709–1712.
ECIRECIR-2010-Collins-ThompsonB #performance #predict #query
Predicting Query Performance via Classification (KCT, PNB), pp. 140–152.
ICMLICML-2010-ChengDH10a #multi
Graded Multilabel Classification: The Ordinal Case (WC, KD, EH), pp. 223–230.
ICMLICML-2010-DembczynskiCH #multi #probability
Bayes Optimal Multilabel Classification via Probabilistic Classifier Chains (KD, WC, EH), pp. 279–286.
ICMLICML-2010-GoldbergE
Boosting Classifiers with Tightened L0-Relaxation Penalties (NG, JE), pp. 383–390.
ICMLICML-2010-HariharanZVV #multi #scalability
Large Scale Max-Margin Multi-Label Classification with Priors (BH, LZM, SVNV, MV), pp. 423–430.
ICMLICML-2010-LayB #predict #using
Supervised Aggregation of Classifiers using Artificial Prediction Markets (NL, AB), pp. 591–598.
ICMLICML-2010-LazaricGM #algorithm #analysis #policy
Analysis of a Classification-based Policy Iteration Algorithm (AL, MG, RM), pp. 607–614.
ICMLICML-2010-Ruping #estimation
SVM Classifier Estimation from Group Probabilities (SR), pp. 911–918.
ICMLICML-2010-TuL #multi
One-sided Support Vector Regression for Multiclass Cost-sensitive Classification (HHT, HTL), pp. 1095–1102.
ICPRICPR-2010-AiHRC #adaptation #component #image #independence
Adaptive Color Independent Components Based SIFT Descriptors for Image Classification (DA, XHH, XR, YWC), pp. 2436–2439.
ICPRICPR-2010-AkbasA #image #low level #segmentation
Low-Level Image Segmentation Based Scene Classification (EA, NA), pp. 3623–3626.
ICPRICPR-2010-AlmaksourAQC #evolution #fuzzy #gesture #incremental #learning #recognition
Evolving Fuzzy Classifiers: Application to Incremental Learning of Handwritten Gesture Recognition Systems (AA, ÉA, SQ, MC), pp. 4056–4059.
ICPRICPR-2010-AndoF #image #segmentation
Human-Area Segmentation by Selecting Similar Silhouette Images Based on Weak-Classifier Response (HA, HF), pp. 3444–3447.
ICPRICPR-2010-ArgunsahC #approach #human-computer #interface
AR-PCA-HMM Approach for Sensorimotor Task Classification in EEG-based Brain-Computer Interfaces (AOA, ), pp. 113–116.
ICPRICPR-2010-BayramDSM #approach
An Ensemble of Classifiers Approach to Steganalysis (SB, AED, HTS, NDM), pp. 4376–4379.
ICPRICPR-2010-BoughorbelBB
Baby-Posture Classification from Pressure-Sensor Data (SB, FB, JB), pp. 556–559.
ICPRICPR-2010-CanavanJRZYS #evaluation #multi
Evaluation of Multi-frame Fusion Based Face Classification Under Shadow (SJC, BJ, MR, YZ, LY, JRS), pp. 1265–1268.
ICPRICPR-2010-CevikalpY #scalability
Large Margin Classifier Based on Affine Hulls (HC, HSY), pp. 21–24.
ICPRICPR-2010-ChenS #nearest neighbour #scalability
Hierarchical Large Margin Nearest Neighbor Classification (QC, SS), pp. 906–909.
ICPRICPR-2010-ChuHC #gender #identification #image #set
Identifying Gender from Unaligned Facial Images by Set Classification (WSC, CRH, CSC), pp. 2636–2639.
ICPRICPR-2010-ConduracheMM #segmentation
An LDA-based Relative Hysteresis Classifier with Application to Segmentation of Retinal Vessels (AC, FM, AM), pp. 4202–4205.
ICPRICPR-2010-CordellaSFMF #performance
Combining Single Class Features for Improving Performance of a Two Stage Classifier (LPC, CDS, FF, CM, ASdF), pp. 4352–4355.
ICPRICPR-2010-DaiYW #image
Three-layer Spatial Sparse Coding for Image Classification (DD, WY, TW), pp. 613–616.
ICPRICPR-2010-DehzangiMCL #fuzzy #using
Framewise Phone Classification Using Weighted Fuzzy Classification Rules (OD, BM, EC, HL), pp. 4186–4189.
ICPRICPR-2010-DesnoyerW #image
Aesthetic Image Classification for Autonomous Agents (MD, DW), pp. 3452–3455.
ICPRICPR-2010-DikmenH #canonical #correlation
Improving Classification Accuracy by Comparing Local Features through Canonical Correlations (MD, TSH), pp. 4032–4035.
ICPRICPR-2010-DornaikaC #detection #performance #using
Efficient Object Detection and Matching Using Feature Classification (FD, FC), pp. 3073–3076.
ICPRICPR-2010-DuGC #web
Enhancing Web Page Classification via Local Co-training (YD, XG, ZC), pp. 2905–2908.
ICPRICPR-2010-DuinOL #multi
Classification of Volcano Events Observed by Multiple Seismic Stations (RPWD, MOA, JMLB), pp. 1052–1055.
ICPRICPR-2010-DukkipatiYM #feature model #modelling
Maximum Entropy Model Based Classification with Feature Selection (AD, AKY, MNM), pp. 565–568.
ICPRICPR-2010-DundarBRJSG #approach #learning #multi #towards
A Multiple Instance Learning Approach toward Optimal Classification of Pathology Slides (MD, SB, VCR, RKJ, OS, MNG), pp. 2732–2735.
ICPRICPR-2010-DurakN #detection #image
Principal Contour Extraction and Contour Classification to Detect Coronal Loops from the Solar Images (ND, ON), pp. 2403–2406.
ICPRICPR-2010-ErdoganS #framework #learning #linear
A Unifying Framework for Learning the Linear Combiners for Classifier Ensembles (HE, MUS), pp. 2985–2988.
ICPRICPR-2010-ErgulA #topic #using
Scene Classification Using Spatial Pyramid of Latent Topics (EE, NA), pp. 3603–3606.
ICPRICPR-2010-FanHM #learning #metric
Learning Metrics for Shape Classification and Discrimination (YF, DH, WM), pp. 2652–2655.
ICPRICPR-2010-FaradjiWB #approach #problem
A Simple Approach to Find the Best Wavelet Basis in Classification Problems (FF, RKW, GEB), pp. 641–644.
ICPRICPR-2010-FornesELV #using
Symbol Classification Using Dynamic Aligned Shape Descriptor (AF, SE, JL, EV), pp. 1957–1960.
ICPRICPR-2010-FuLTZ #learning #music #naive bayes #retrieval
Learning Naive Bayes Classifiers for Music Classification and Retrieval (ZF, GL, KMT, DZ), pp. 4589–4592.
ICPRICPR-2010-GargiuloS #network #performance
Improving Performance of Network Traffic Classification Systems by Cleaning Training Data (FG, CS), pp. 2768–2771.
ICPRICPR-2010-GhanemVW #multi
Multi-class Pattern Classification in Imbalanced Data (ASG, SV, GAWW), pp. 2881–2884.
ICPRICPR-2010-GordoP #approach #documentation #multi
A Bag-of-Pages Approach to Unordered Multi-page Document Classification (AG, FP), pp. 1920–1923.
ICPRICPR-2010-HafnerGLUVW #image #using
Endoscopic Image Classification Using Edge-Based Features (MH, AG, ML, AU, AV, FW), pp. 2724–2727.
ICPRICPR-2010-HanL #biology #multi
A Hierarchical GIST Model Embedding Multiple Biological Feasibilities for Scene Classification (YH, GL), pp. 3109–3112.
ICPRICPR-2010-HeG
Rare Class Classification by Support Vector Machine (HH, AG), pp. 548–551.
ICPRICPR-2010-Hotta #using #visual notation #word
Scene Classification Using Local Co-occurrence Feature in Subspace Obtained by KPCA of Local Blob Visual Words (KH), pp. 4230–4233.
ICPRICPR-2010-HuangDF #estimation #multi #random
Head Pose Estimation Based on Random Forests for Multiclass Classification (CH, XD, CF), pp. 934–937.
ICPRICPR-2010-HuangWFBHL #multimodal
Multimodal Sleeping Posture Classification (WH, AAPW, FSF, JB, CCH, KL), pp. 4336–4339.
ICPRICPR-2010-HuWZW #gender
Combining Spatial and Temporal Information for Gait Based Gender Classification (MH, YW, ZZ, YW), pp. 3679–3682.
ICPRICPR-2010-IdeSDTM #video
Classification of Near-Duplicate Video Segments Based on Their Appearance Patterns (II, YS, DD, TT, HM), pp. 3129–3133.
ICPRICPR-2010-ImpedovoP #evaluation #generative #multi #set
Generating Sets of Classifiers for the Evaluation of Multi-expert Systems (DI, GP), pp. 2166–2169.
ICPRICPR-2010-JabidKC #gender #using
Gender Classification Using Local Directional Pattern (LDP) (TJ, MHK, OC), pp. 2162–2165.
ICPRICPR-2010-JakkojuKJ #performance #using
Fast and Spatially-Smooth Terrain Classification Using Monocular Camera (CJ, KMK, CVJ), pp. 4060–4063.
ICPRICPR-2010-JiangWXD #image
A New Biologically Inspired Feature for Scene Image Classification (AJ, CW, BX, RD), pp. 758–761.
ICPRICPR-2010-JunG #process
Nearest-Manifold Classification with Gaussian Processes (GJ, JG), pp. 914–917.
ICPRICPR-2010-KhreichGMS
Boolean Combination of Classifiers in the ROC Space (WK, EG, AM, RS), pp. 4299–4303.
ICPRICPR-2010-KimM #dataset
Dense Structure Inference for Object Classification in Aerial LIDAR Dataset (EK, GGM), pp. 3049–3052.
ICPRICPR-2010-KobayashiO10a #image
Bag of Hierarchical Co-occurrence Features for Image Classification (TK, NO), pp. 3882–3885.
ICPRICPR-2010-KotropoulosAP #music
Ensemble Discriminant Sparse Projections Applied to Music Genre Classification (CK, GRA, YP), pp. 822–825.
ICPRICPR-2010-KrajewskiBK #case study #detection #multi #self #speech
Comparing Multiple Classifiers for Speech-Based Detection of Self-Confidence — A Pilot Study (JK, AB, SK), pp. 3716–3719.
ICPRICPR-2010-KuksaP #performance #representation #sequence
Spatial Representation for Efficient Sequence Classification (PPK, VP), pp. 3320–3323.
ICPRICPR-2010-KumarCCAPH #complexity #using
Heart Murmur Classification Using Complexity Signatures (DK, PC, RC, MA, RPP, JH), pp. 2564–2567.
ICPRICPR-2010-LawalAM #abduction #network #recognition #using
Recognition of Handwritten Arabic (Indian) Numerals Using Freeman’s Chain Codes and Abductive Network Classifiers (IAL, REAA, SAM), pp. 1884–1887.
ICPRICPR-2010-LeECA #case study
A Study of Voice Source and Vocal Tract Filter Based Features in Cognitive Load Classification (PNL, JE, EHCC, EA), pp. 4516–4519.
ICPRICPR-2010-LeeWC #linear #multi
A Discriminative and Heteroscedastic Linear Feature Transformation for Multiclass Classification (HSL, HMW, BC), pp. 690–693.
ICPRICPR-2010-LiD #multi #verification
Multi-classifier Q-stack Aging Model for Adult Face Verification (WL, AD), pp. 1310–1313.
ICPRICPR-2010-LiGZ #representation
Local Sparse Representation Based Classification (CGL, JG, HGZ), pp. 649–652.
ICPRICPR-2010-LiP10a #analysis #monitoring #realtime
Human State Classification and Predication for Critical Care Monitoring by Real-Time Bio-signal Analysis (XL, FP), pp. 2460–2463.
ICPRICPR-2010-Liu10a #prototype #retrieval
One-Vs-All Training of Prototype Classifier for Pattern Classification and Retrieval (CLL), pp. 3328–3331.
ICPRICPR-2010-LiuC #image #string
Spatial String Matching for Image Classification (YL, VC), pp. 2937–2940.
ICPRICPR-2010-LopesGKO #music
Selection of Training Instances for Music Genre Classification (ML, FG, ALK, LESdO), pp. 4569–4572.
ICPRICPR-2010-LotteG
Spatially Regularized Common Spatial Patterns for EEG Classification (FL, CG), pp. 3712–3715.
ICPRICPR-2010-LuLLY #automation #image
Automated Cell Phase Classification for Zebrafish Fluorescence Microscope Images (YL, JL, TL, JY), pp. 2584–2587.
ICPRICPR-2010-LuoN #fault #learning #multi #problem
Employing Decoding of Specific Error Correcting Codes as a New Classification Criterion in Multiclass Learning Problems (YL, KN), pp. 4238–4241.
ICPRICPR-2010-MahdhaouiC #multi #speech
Emotional Speech Classification Based on Multi View Characterization (AM, MC), pp. 4488–4491.
ICPRICPR-2010-MangalampalliCS #fuzzy #image #named #performance
I-FAC: Efficient Fuzzy Associative Classifier for Object Classes in Images (AM, VC, SS), pp. 4388–4391.
ICPRICPR-2010-ManjunathMS #database #relational
A Practical Heterogeneous Classifier for Relational Databases (GM, MNM, DS), pp. 3316–3319.
ICPRICPR-2010-Martin-HerreroF #question
Tensor-Driven Hyperspectral Denoising: A Strong Link for Classification Chains? (JMH, MFA), pp. 2820–2823.
ICPRICPR-2010-MelendezPG #adaptation #on the #segmentation
On Adapting Pixel-based Classification to Unsupervised Texture Segmentation (JM, DP, MAG), pp. 854–857.
ICPRICPR-2010-MozaffariBA #gender #geometry #image #using
Gender Classification Using Single Frontal Image Per Person: Combination of Appearance and Geometric Based Features (SM, HB, RA), pp. 1192–1195.
ICPRICPR-2010-NguyenJA #automation #image #segmentation
Automated Gland Segmentation and Classification for Gleason Grading of Prostate Tissue Images (KN, AKJ, RLA), pp. 1497–1500.
ICPRICPR-2010-NicolaouGP
Audio-Visual Classification and Fusion of Spontaneous Affective Data in Likelihood Space (MAN, HG, MP), pp. 3695–3699.
ICPRICPR-2010-OzdemirA #image #representation #using
Image Classification Using Subgraph Histogram Representation (, SA), pp. 1112–1115.
ICPRICPR-2010-PaclikLLD #analysis #optimisation
ROC Analysis and Cost-Sensitive Optimization for Hierarchical Classifiers (PP, CL, TL, RPWD), pp. 2977–2980.
ICPRICPR-2010-PapaCF #dataset #optimisation
Optimizing Optimum-Path Forest Classification for Huge Datasets (JPP, FAMC, AXF), pp. 4162–4165.
ICPRICPR-2010-Parker #empirical #feature model
An Empirical Study of Feature Extraction Methods for Audio Classification (CP), pp. 4593–4596.
ICPRICPR-2010-PengSGS #documentation #using
Text Separation from Mixed Documents Using a Tree-Structured Classifier (XP, SS, VG, RS), pp. 241–244.
ICPRICPR-2010-PengYZC #segmentation #using
Retinal Blood Vessels Segmentation Using the Radial Projection and Supervised Classification (QP, XY, LZ, YmC), pp. 1489–1492.
ICPRICPR-2010-PhilippotBB #algorithm #learning #network #online
Bayesian Networks Learning Algorithms for Online Form Classification (EP, YB, AB), pp. 1981–1984.
ICPRICPR-2010-PiroNNB
Boosting Bayesian MAP Classification (PP, RN, FN, MB), pp. 661–665.
ICPRICPR-2010-PlumptonKLJ #linear #online #using
On-Line fMRI Data Classification Using Linear and Ensemble Classifiers (COP, LIK, DEJL, SJJ), pp. 4312–4315.
ICPRICPR-2010-RichiardiVRB #graph #sequence
Vector Space Embedding of Undirected Graphs with Fixed-cardinality Vertex Sequences for Classification (JR, DVDV, KR, HB), pp. 902–905.
ICPRICPR-2010-Sarkar #documentation #image #learning
Learning Image Anchor Templates for Document Classification and Data Extraction (PS), pp. 3428–3431.
ICPRICPR-2010-Sato #design #kernel #learning
A New Learning Formulation for Kernel Classifier Design (AS), pp. 2897–2900.
ICPRICPR-2010-SchelsS #approach #image #multi #sequence
A Multiple Classifier System Approach for Facial Expressions in Image Sequences Utilizing GMM Supervectors (MS, FS), pp. 4251–4254.
ICPRICPR-2010-SeoAD #evaluation #performance #segmentation #tool support
Performance Evaluation Tools for Zone Segmentation and Classification (PETS) (WS, MA, DSD), pp. 503–506.
ICPRICPR-2010-SeyedhosseiniPT #image #network #parsing
Image Parsing with a Three-State Series Neural Network Classifier (MS, ARCP, TT), pp. 4508–4511.
ICPRICPR-2010-ShibataKI #nearest neighbour #performance #scalability
Large Margin Discriminant Hashing for Fast k-Nearest Neighbor Classification (TS, SK, SI), pp. 1015–1018.
ICPRICPR-2010-ShivakumaraDTP #proximity #symmetry #video
A New Symmetry Based on Proximity of Wavelet-Moments for Text Frame Classification in Video (PS, AD, CLT, UP), pp. 129–132.
ICPRICPR-2010-ShivakumaraT #novel #video
Novel Edge Features for Text Frame Classification in Video (PS, CLT), pp. 3191–3194.
ICPRICPR-2010-ShobeirinejadG #gender #using
Gender Classification Using Interlaced Derivative Patterns (AS, YG), pp. 1509–1512.
ICPRICPR-2010-SilvaLSBKT #documentation
Enhancing the Filtering-Out of the Back-to-Front Interference in Color Documents with a Neural Classifier (GdFPeS, RDL, JMS, SB, AK, MT), pp. 2415–2419.
ICPRICPR-2010-Simsekli #automation #music #using
Automatic Music Genre Classification Using Bass Lines (US), pp. 4137–4140.
ICPRICPR-2010-SternigRB #learning #multi
Inverse Multiple Instance Learning for Classifier Grids (SS, PMR, HB), pp. 770–773.
ICPRICPR-2010-StuhlsatzLZ #feature model
Feature Extraction for Simple Classification (AS, JL, TZ), pp. 1525–1528.
ICPRICPR-2010-SzczotFLP #adaptation
Package Boosting for Readaption of Cascaded Classifiers (MS, JF, OL, GP), pp. 552–555.
ICPRICPR-2010-TakahashiK #approximate
Margin Preserved Approximate Convex Hulls for Classification (TT, MK), pp. 4052–4055.
ICPRICPR-2010-Thurau #scalability
Nearest Archetype Hull Methods for Large-Scale Data Classification (CT), pp. 4040–4043.
ICPRICPR-2010-TimmM #fault #fourier #image #statistics
Statistical Fourier Descriptors for Defect Image Classification (FT, TM), pp. 4190–4193.
ICPRICPR-2010-TumaIP #kernel #set #using
Hydroacoustic Signal Classification Using Kernel Functions for Variable Feature Sets (MT, CI, MP), pp. 1011–1014.
ICPRICPR-2010-TurkerKG #image #network #using
Classification of Polarimetric SAR Images Using Evolutionary RBF Networks (TI, SK, MG), pp. 4324–4327.
ICPRICPR-2010-WangH10a #case study #design #multi #prototype #using
A Study of Designing Compact Recognizers of Handwritten Chinese Characters Using Multiple-Prototype Based Classifiers (YW, QH), pp. 1872–1875.
ICPRICPR-2010-WangSLYB #using
Shape Classification Using Tree -Unions (BW, WS, WL, XY, XB), pp. 983–986.
ICPRICPR-2010-Williams
Underwater Mine Classification with Imperfect Labels (DPW), pp. 4157–4161.
ICPRICPR-2010-WojcikiewiczBK #clustering #image
Enhancing Image Classification with Class-wise Clustered Vocabularies (WW, AB, MK), pp. 1060–1063.
ICPRICPR-2010-WoloszynskiK #random
A Measure of Competence Based on Randomized Reference Classifier for Dynamic Ensemble Selection (TW, MK), pp. 4194–4197.
ICPRICPR-2010-XiaoZZS #multi
Data Classification on Multiple Manifolds (RX, QZ, DZ, PS), pp. 3898–3901.
ICPRICPR-2010-YangC #representation
Sparse Representation Classifier Steered Discriminative Projection (JY, DC), pp. 694–697.
ICPRICPR-2010-YinAB
Imbalance and Concentration in k-NN Classification (DY, CA, HSB), pp. 2170–2173.
ICPRICPR-2010-YukselG #detection
Variational Mixture of Experts for Classification with Applications to Landmine Detection (SEY, PDG), pp. 2981–2984.
ICPRICPR-2010-ZhangSW #online
A SVM-HMM Based Online Classifier for Handwritten Chemical Symbols (YZ, GS, KW), pp. 1888–1891.
ICPRICPR-2010-ZhangWB #using
Age Classification Base on Gait Using HMM (DZ, YW, BB), pp. 3834–3837.
ICPRICPR-2010-ZhangZYK #detection #learning #representation #taxonomy
Microaneurysm (MA) Detection via Sparse Representation Classifier with MA and Non-MA Dictionary Learning (BZ, LZ, JY, FK), pp. 277–280.
ICPRICPR-2010-ZhangZZLL #enterprise #kernel
Gaussian ERP Kernel Classifier for Pulse Waveforms Classification (DZ, WZ, DZ, YL, NL), pp. 2736–2739.
ICPRICPR-2010-ZhangZZZ #kernel #metric #using
Time Series Classification Using Support Vector Machine with Gaussian Elastic Metric Kernel (DZ, WZ, DZ, HZ), pp. 29–32.
ICPRICPR-2010-ZhouCW #network #quantum
Deep Quantum Networks for Classification (SZ, QC, XW), pp. 2885–2888.
KDDKDD-2010-AttenbergP #learning #modelling #why
Why label when you can search?: alternatives to active learning for applying human resources to build classification models under extreme class imbalance (JA, FJP), pp. 423–432.
KDDKDD-2010-DurrantK #analysis #linear
Compressed fisher linear discriminant analysis: classification of randomly projected data (RJD, AK), pp. 1119–1128.
KDDKDD-2010-FeiH #functional #graph
Boosting with structure information in the functional space: an application to graph classification (HF, JH), pp. 643–652.
KDDKDD-2010-KongY #feature model #graph
Semi-supervised feature selection for graph classification (XK, PSY), pp. 793–802.
KDDKDD-2010-Lee #learning
Learning to combine discriminative classifiers: confidence based (CHL), pp. 743–752.
KDDKDD-2010-PrengerLVCH #bound #fault
Class-specific error bounds for ensemble classifiers (RJP, TDL, KRV, BYC, WGH), pp. 843–852.
KDDKDD-2010-RaykarKY #design #performance #trade-off
Designing efficient cascaded classifiers: tradeoff between accuracy and cost (VCR, BK, SY), pp. 853–860.
KDDKDD-2010-YanFDR
Medical coding classification by leveraging inter-code relationships (YY, GF, JGD, RR), pp. 193–202.
KDDKDD-2010-YangJJZT #categorisation
Unsupervised transfer classification: application to text categorization (TY, RJ, AKJ, YZ, WT), pp. 1159–1168.
KDDKDD-2010-YuHCL #in memory #linear #memory management #scalability
Large linear classification when data cannot fit in memory (HFY, CJH, KWC, CJL), pp. 833–842.
KDIRKDIR-2010-MuA #graph #multi
Proximity-based Graph Embeddings for Multi-label Classification (TM, SA), pp. 74–84.
KDIRKDIR-2010-Onem #behaviour #detection #network
Unwanted Behaviour Detection and Classification in Network Traffic (IMÖ), pp. 122–128.
KDIRKDIR-2010-Pavlovic-LazeticG #concept #documentation
Ontology-driven Conceptual Document Classification (GPL, JG), pp. 383–386.
KDIRKDIR-2010-Schoneberg #evaluation
Context Vector Classification — Term Classification with Context Evaluation (HS), pp. 387–391.
KDIRKDIR-2010-TsengPF #markov #using
The Typhoon Track Classification using Tri-plots and Markov Chain (JCHT, HKKP, CF), pp. 364–369.
KDIRKDIR-2010-ViswanathBK #nearest neighbour #performance #set
A Method to Generate a Reduced Training Set for Faster and Better Nearest Neighbor Classification (PV, VSB, TNK), pp. 232–236.
KEODKEOD-2010-Alfort #approach #information retrieval
Scale and the Classificatory Dimension — A Linguistic Approach to Contextual IR (EA), pp. 370–373.
KEODKEOD-2010-ChatterjeeKRD #automation #email #ontology #using
Automatic Email Classification using user Preference Ontology (NC, SK, SR, VD), pp. 165–170.
KEODKEOD-2010-FukumotoS #identification
Identifying Domain-specific Senses and Its Application to Text Classification (FF, YS), pp. 263–268.
KEODKEOD-2010-MollerSBEDS #owl #representation
Representing the International Classification of Diseases Version 10 in OWL (MM, MS, RB, PE, AD, DS), pp. 50–59.
SEKESEKE-2010-MauczkaBG #case study #metric #process
Analyzing the Relationship of Process Metrics And Classified Changes — A Pilot Study (AM, MB, TG), pp. 269–272.
SEKESEKE-2010-SilvaS #data mining #knowledge base #mining #modelling #relational #testing
Modeling and Testing a Knowledge Base for Instructing Users to Choose the Classification Task in Relational Data Mining (LMdS, AEAdS), pp. 608–613.
SEKESEKE-2010-WangKG #feature model #quality
Ensemble Feature Selection Technique for Software Quality Classification (HW, TMK, KG), pp. 215–220.
SEKESEKE-2010-XuanJRYL #automation #debugging #using
Automatic Bug Triage using Semi-Supervised Text Classification (JX, HJ, ZR, JY, ZL), pp. 209–214.
SIGIRSIGIR-2010-AwadallahRW
Language-model-based pro/con classification of political text (RA, MR, GW), pp. 747–748.
SIGIRSIGIR-2010-ChenYLZQ #personalisation #predict #query #question
Predicting query potential for personalization, classification or regression? (CC, MY, SL, TZ, HQ), pp. 725–726.
SIGIRSIGIR-2010-CuiZC #video #web
Content-enriched classifier for web video classification (BC, CZ, GC), pp. 619–626.
SIGIRSIGIR-2010-GoharianM #query #using
Context aware query classification using dynamic query window and relationship net (NG, SSRM), pp. 723–724.
SIGIRSIGIR-2010-GopalY #multi
Multilabel classification with meta-level features (SG, YY), pp. 315–322.
SIGIRSIGIR-2010-HongSBWJ #probability
A joint probabilistic classification model for resource selection (DH, LS, PB, MW, TJ), pp. 98–105.
SIGIRSIGIR-2010-HuangAH #recommendation #tool support
Medical search and classification tools for recommendation (XH, AA, QH), p. 707.
SIGIRSIGIR-2010-LiNCL #image
Entropy descriptor for image classification (HL, JN, JC, HL), pp. 753–754.
SIGIRSIGIR-2010-SallesRPMMG #algorithm #documentation
Temporally-aware algorithms for document classification (TS, LCdR, GLP, FM, WMJ, MAG), pp. 307–314.
SIGIRSIGIR-2010-SriramFDFD #information management #twitter
Short text classification in twitter to improve information filtering (BS, DF, ED, HF, MD), pp. 841–842.
SIGIRSIGIR-2010-ZhenY #design #named
SED: supervised experimental design and its application to text classification (YZ, DYY), pp. 299–306.
SPLCSPLC-2010-TekinerdoganTS #approach #multi #product line
Multidimensional Classification Approach for Defining Product Line Engineering Transition Strategies (BT, ET, ES), pp. 461–465.
SACSAC-2010-BicegoLOP #array #modelling #topic #using
Expression microarray classification using topic models (MB, PL, BO, AP), pp. 1516–1520.
SACSAC-2010-CascaranoCR
Improving cost and accuracy of DPI traffic classifiers (NC, LC, FR), pp. 641–646.
SACSAC-2010-ChandaFP #documentation
Structural handwritten and machine print classification for sparse content and arbitrary oriented document fragments (SC, KF, UP), pp. 18–22.
SACSAC-2010-DelisVT #approach
A data perturbation approach to sensitive classification rule hiding (AD, VSV, AAT), pp. 605–609.
SACSAC-2010-FernandesLR #random
The impact of random samples in ensemble classifiers (PF, LL, DDAR), pp. 1002–1009.
SACSAC-2010-GaberS #data type #distributed #network
Distributed data stream classification for wireless sensor networks (MMG, AMS), pp. 1629–1630.
SACSAC-2010-GuermaziHH #analysis #image #using #web
Classification of violent web images using context based analysis (RG, MH, ABH), pp. 1768–1773.
SACSAC-2010-HanFD #correlation #recognition
A discriminated correlation classifier for face recognition (ZH, CF, XD), pp. 1485–1490.
SACSAC-2010-HeraviZ #case study #metric
A study on interestingness measures for associative classifiers (MJH, ORZ), pp. 1039–1046.
SACSAC-2010-LanLSH #algorithm #image #using
An improved K-view algorithm for image texture classification using new characteristic views selection methods (YL, HL, ES, CCH), pp. 959–963.
SACSAC-2010-MenorBBGP #markov #taxonomy #using
Virus DNA-fragment classification using taxonomic hidden Markov model profiles (MM, KB, MB, YG, GP), pp. 1567–1571.
SACSAC-2010-OhCM #information management
Combining global and local information for enhanced deep classification (HSO, YC, SHM), pp. 1760–1767.
SACSAC-2010-QinXL #nondeterminism
A Bayesian classifier for uncertain data (BQ, YX, FL), pp. 1010–1014.
SACSAC-2010-SillaKK #automation #hybrid #music
Improving automatic music genre classification with hybrid content-based feature vectors (CNSJ, ALK, CAAK), pp. 1702–1707.
SACSAC-2010-ZhangW #image #representation
Image representation and classification based on data compression (NZ, TW), pp. 981–982.
CASECASE-2010-ParkSR #automation #database
Image-based automated chemical database annotation with ensemble of machine-vision classifiers (JP, KS, GRR), pp. 168–173.
DACDAC-2010-CallegariDWA #learning #using
Classification rule learning using subgroup discovery of cross-domain attributes responsible for design-silicon mismatch (NC, DGD, LCW, MSA), pp. 374–379.
PDPPDP-2010-Ulltveit-MoeO #privacy
Privacy Violation Classification of Snort Ruleset (NUM, VAO), pp. 654–658.
ESOPESOP-2010-AskarovM #framework #semantics
A Semantic Framework for Declassification and Endorsement (AA, AM), pp. 64–84.
CBSECBSE-2009-BirkmeierO #comparison #component #identification #on the #state of the art
On Component Identification Approaches — Classification, State of the Art, and Comparison (DB, SO), pp. 1–18.
WICSA-ECSAWICSA-ECSA-2009-AboudAFHTUV #architecture #automation #component #concept #using
Automated architectural component classification using concept lattices (NAA, GA, JRF, MH, CT, CU, SV), pp. 21–30.
WICSA-ECSAWICSA-ECSA-2009-AngelovGG #architecture #effectiveness
A classification of software reference architectures: Analyzing their success and effectiveness (SA, PWPJG, DG), pp. 141–150.
DocEngDocEng-2009-ZubiagaMF #social #web
Getting the most out of social annotations for web page classification (AZ, RM, VF), pp. 74–83.
DRRDRR-2009-Likforman-SulemS #network #recognition
Combination of dynamic Bayesian network classifiers for the recognition of degraded characters (LLS, MS), pp. 1–10.
DRRDRR-2009-NonnemakerB #using
Using synthetic data safely in classification (JN, HSB), pp. 1–10.
DRRDRR-2009-Obafemi-AjayiAF #documentation #image #performance
Efficient shape-LUT classification for document image restoration (TOA, GA, OF), pp. 1–10.
ICDARICDAR-2009-AlaeiNP
Fine Classification of Unconstrained Handwritten Persian/Arabic Numerals by Removing Confusion amongst Similar Classes (AA, PN, UP), pp. 601–605.
ICDARICDAR-2009-AlyUFS #statistics
Statistical Classification of Spatial Relationships among Mathematical Symbols (WA, SU, AF, MS), pp. 1350–1354.
ICDARICDAR-2009-EmmanouilidisBP #development #evaluation #locality
Development and Evaluation of Text Localization Techniques Based on Structural Texture Features and Neural Classifiers (CE, CB, NP), pp. 1270–1274.
ICDARICDAR-2009-GordoV #documentation #invariant #layout #retrieval
A Rotation Invariant Page Layout Descriptor for Document Classification and Retrieval (AG, EV), pp. 481–485.
ICDARICDAR-2009-HeH09a #estimation #online #using
Affine Distortion Compensation for an Isolated Online Handwritten Chinese Character Using Combined Orientation Estimation and HMM-Based Minimax Classification (TH, QH), pp. 1226–1230.
ICDARICDAR-2009-LandreMR #difference #image #using
Ornamental Letters Image Classification Using Local Dissimilarity Maps (JL, FMN, SR), pp. 186–190.
ICDARICDAR-2009-LinsSSFSST #documentation #image #quality
Image Classification to Improve Printing Quality of Mixed-Type Documents (RDL, GPeS, SJS, JF, MQS, PS, MT), pp. 1106–1110.
ICDARICDAR-2009-LuqmanBR #graph #network #recognition #using
Graphic Symbol Recognition Using Graph Based Signature and Bayesian Network Classifier (MML, TB, JYR), pp. 1325–1329.
ICDARICDAR-2009-MansjurWJ #automation #categorisation #kernel #learning #topic #using
Using Kernel Density Classifier with Topic Model and Cost Sensitive Learning for Automatic Text Categorization (DSM, TSW, BHJ), pp. 1086–1090.
ICDARICDAR-2009-MaruyamaY #image
Extraction of Characters on Signboards in Natural Scene Images by Stump Classifiers (MM, TY), pp. 1365–1369.
ICDARICDAR-2009-MoghaddamC #automation #clustering #documentation #image #multi #word
Application of Multi-Level Classifiers and Clustering for Automatic Word Spotting in Historical Document Images (RFM, MC), pp. 511–515.
ICDARICDAR-2009-MoghaddamRC #approach #independence #multi #segmentation #set #using
Restoration and Segmentation of Highly Degraded Characters Using a Shape-Independent Level Set Approach and Multi-level Classifiers (RFM, DRH, MC), pp. 828–832.
ICDARICDAR-2009-PalWK #case study #comparative #recognition #using
Comparative Study of Devnagari Handwritten Character Recognition Using Different Feature and Classifiers (UP, TW, FK), pp. 1111–1115.
ICDARICDAR-2009-PereiraC #prototype
Prototype Selection for Handwritten Connected Digits Classification (CdSP, GDCC), pp. 1021–1025.
ICDARICDAR-2009-PirloITS #normalisation
Combination of Measurement-Level Classifiers: Output Normalization by Dynamic Time Warping (GP, DI, CAT, ES), pp. 416–420.
ICDARICDAR-2009-PirloTI #multi
A Feedback-Based Multi-Classifier System (GP, CAT, DI), pp. 713–717.
ICDARICDAR-2009-RoyMSS #adaptation #framework #online #recognition
A Framework for Adaptation of the Active-DTW Classifier for Online Handwritten Character Recognition (VR, SM, AS, RRS), pp. 401–405.
ICDARICDAR-2009-SidereHR #graph #representation
Vector Representation of Graphs: Application to the Classification of Symbols and Letters (NS, PH, JYR), pp. 681–685.
ICDARICDAR-2009-StefanoFFM #evolution #learning #network
Learning Bayesian Networks by Evolution for Classifier Combination (CDS, FF, ASdF, AM), pp. 966–970.
ICDARICDAR-2009-VamvakasGP #documentation #feature model #novel #recognition
A Novel Feature Extraction and Classification Methodology for the Recognition of Historical Documents (GV, BG, SJP), pp. 491–495.
ICDARICDAR-2009-WangH #design #fault #modelling #parametricity #precise #using
Design Compact Recognizers of Handwritten Chinese Characters Using Precision Constrained Gaussian Models, Minimum Classification Error Training and Parameter Compression (YW, QH), pp. 36–40.
ICDARICDAR-2009-Washizawa #metric
Pattern Classification on Local Metric Structure (YW), pp. 471–475.
ICDARICDAR-2009-XuSGN #categorisation #documentation
A Hierarchical Classification Model for Document Categorization (JWX, VS, VG, DN), pp. 486–490.
ICDARICDAR-2009-YinHTSN #multi #recognition
Rejection Strategies with Multiple Classifiers for Handwritten Character Recognition (XCY, HWH, YFT, JS, SN), pp. 1126–1130.
ICDARICDAR-2009-ZhuSMHN #feature model
Separate Chinese Character and English Character by Cascade Classifier and Feature Selection (YZ, JS, AM, YH, SN), pp. 1191–1195.
VLDBVLDB-2009-MozafariZ #naive bayes #privacy
Publishing Naive Bayesian Classifiers: Privacy without Accuracy Loss (BM, CZ), pp. 1173–1185.
EDMEDM-2009-HeinerZ #student
Improving Student Question Classification (CH, JLZ), pp. 259–268.
ITiCSEITiCSE-2009-SkupasDR #programming
Developing classification criteria for programming tasks (BS, VD, MAR), p. 373.
ICSMEICSM-2009-FerzundAW #metric #using
Software change classification using hunk metrics (JF, SNA, FW), pp. 471–474.
TLCATLCA-2009-TsukadaI #logic
A Logical Foundation for Environment Classifiers (TT, AI), pp. 341–355.
DiGRADiGRA-2009-DahlskogKA #functional #game studies #using
Mapping the game landscape: Locating genres using functional classification (SD, AK, EA).
CHICHI-2009-TalbotLKT #interactive #machine learning #multi #named #visualisation
EnsembleMatrix: interactive visualization to support machine learning with multiple classifiers (JT, BL, AK, DST), pp. 1283–1292.
HCIDHM-2009-JeonJKH #gender #using
Facial Gender Classification Using LUT-Based Sub-images and DIE (JBJ, SHJ, DJK, KSH), pp. 36–45.
HCIHCI-NIMT-2009-JohnsonK
Ensemble SWLDA Classifiers for the P300 Speller (GDJ, DJK), pp. 551–557.
HCIHCI-NIMT-2009-MurakamiK #music
Study of Feature Values for Subjective Classification of Music (MM, TK), pp. 701–709.
HCIHCI-NT-2009-LiuUC #3d #interface
Goods-Finding and Orientation in the Elderly on 3D Virtual Store Interface: The Impact of Classification and Landmarks (CLL, STU, CHC), pp. 474–483.
HCIHIMI-DIE-2009-IshibashiN
Metadata-Based Reminder Classification in Reminiscence Engineering (MI, YN), pp. 412–418.
HCIHIMI-DIE-2009-SrinivasSPK #feature model #performance #using
Efficient Text Classification Using Best Feature Selection and Combination of Methods (MS, KPS, EVP, SAK), pp. 437–446.
ICEISICEIS-AIDSS-2009-TamargoGABQ
Decision Support System for Classification of Natural Risk in Maritime Construction (MAGT, ASAG, VCA, ABT, AAQ), pp. 138–143.
ICEISICEIS-AIDSS-2009-ZhengZLL #case study #image #multi
Study on Image Classification based on SVM and the Fusion of Multiple Features (DZ, TZ, SL, YL), pp. 80–84.
ICEISICEIS-J-2009-ChangS #analysis #performance
Fast Unsupervised Classification for Handwritten Stroke Analysis (WDC, JS), pp. 918–927.
ICEISICEIS-J-2009-GhezziRB #delivery #mobile #platform
A Technology Classification Model for Mobile Content and Service Delivery Platforms (AG, FR, RB), pp. 600–614.
ICEISICEIS-J-2009-GimenezHL
A Hierarchical Product-Property Model to Support Product Classification and Manage Structural and Planning Data (DMG, GPH, HPL), pp. 639–650.
ICEISICEIS-J-2009-PapatheocharousA #fuzzy #predict
Classification and Prediction of Software Cost through Fuzzy Decision Trees (EP, ASA), pp. 234–247.
ICEISICEIS-J-2009-SchclarR #random
Random Projection Ensemble Classifiers (AS, LR), pp. 309–316.
ICEISICEIS-SAIC-2009-LeeLK #using
Blog Classification using K-means (KJL, ML, WK), pp. 61–67.
CIKMCIKM-2009-ArguelloCD
Classification-based resource selection (JA, JC, FD), pp. 1277–1286.
CIKMCIKM-2009-BatalH #using
Boosting KNN text classification accuracy by using supervised term weighting schemes (IB, MH), pp. 2041–2044.
CIKMCIKM-2009-CaoSXHYC #named #personalisation #query
PQC: personalized query classification (BC, JTS, EWX, DHH, QY, ZC), pp. 1217–1226.
CIKMCIKM-2009-ChenLQZ
Instance- and bag-level manifold regularization for aggregate outputs classification (SC, BL, MQ, CZ), pp. 1593–1596.
CIKMCIKM-2009-ChenTJ #detection #framework #social #social media #web
A co-classification framework for detecting web spam and spammers in social media web sites (FC, PNT, AKJ), pp. 1807–1810.
CIKMCIKM-2009-ChinavleKOF
Ensembles in adversarial classification for spam (DC, PK, TO, TF), pp. 2015–2018.
CIKMCIKM-2009-GargS #learning
Active learning in partially supervised classification (PG, SS), pp. 1783–1786.
CIKMCIKM-2009-HolzeGR #consistency #online
Consistent on-line classification of dbs workload events (MH, CG, NR), pp. 1641–1644.
CIKMCIKM-2009-JinYW #graph
Graph classification based on pattern co-occurrence (NJ, CY, WW), pp. 573–582.
CIKMCIKM-2009-KimPDG #graph #web
Improving web page classification by label-propagation over click graphs (SMK, PP, LD, SG), pp. 1077–1086.
CIKMCIKM-2009-KobayakawaKTOKT #analysis #kernel #using
Opinion classification with tree kernel SVM using linguistic modality analysis (TSK, TK, HT, NO, JDK, JT), pp. 1791–1794.
CIKMCIKM-2009-LiuZ #sentiment #using
Cross-domain sentiment classification using a two-stage method (KL, JZ), pp. 1717–1720.
CIKMCIKM-2009-MartineauFJP #difference #problem #using #word
Improving binary classification on text problems using differential word features (JM, TF, AJ, SP), pp. 2019–2024.
CIKMCIKM-2009-QiuZHZ #named #self #sentiment
SELC: a self-supervised model for sentiment classification (LQ, WZ, CH, KZ), pp. 929–936.
CIKMCIKM-2009-ShenLLZ #query
Product query classification (DS, YL, XL, DZ), pp. 741–750.
CIKMCIKM-2009-ShenWCSYCL
Exploiting term relationship to boost text classification (DS, JW, BC, JTS, QY, ZC, YL), pp. 1637–1640.
CIKMCIKM-2009-SunLL #case study #category theory #performance #predict #what
What makes categories difficult to classify?: a study on predicting classification performance for categories (AS, EPL, YL), pp. 1891–1894.
CIKMCIKM-2009-XiongLZLFZZ #information management #named #online #web
OfCourse: web content discovery, classification and information extraction for online course materials (YX, PL, YZ, FL, SF, BZ, LZ), pp. 2077–2078.
ECIRECIR-2009-EsuliS #learning #multi
Active Learning Strategies for Multi-Label Text Classification (AE, FS), pp. 102–113.
ECIRECIR-2009-EsuliS09a #encoding
Encoding Ordinal Features into Binary Features for Text Classification (AE, FS), pp. 771–775.
ECIRECIR-2009-GanstererP #email
E-Mail Classification for Phishing Defense (WNG, DP), pp. 449–460.
ECIRECIR-2009-Pablo-SanchezM #graph
Building a Graph of Names and Contextual Patterns for Named Entity Classification (CdPS, PM), pp. 530–537.
ICMLICML-2009-Cesa-BianchiGO #bound #robust
Robust bounds for classification via selective sampling (NCB, CG, FO), pp. 121–128.
ICMLICML-2009-DuanTXC #adaptation #multi
Domain adaptation from multiple sources via auxiliary classifiers (LD, IWT, DX, TSC), pp. 289–296.
ICMLICML-2009-GermainLLM #learning #linear
PAC-Bayesian learning of linear classifiers (PG, AL, FL, MM), pp. 353–360.
ICMLICML-2009-KeglB
Boosting products of base classifiers (BK, RBF), pp. 497–504.
ICMLICML-2009-Li #adaptation #multi #named
ABC-boost: adaptive base class boost for multi-class classification (PL0), pp. 625–632.
ICMLICML-2009-PlathTN #image #multi #random #segmentation #using
Multi-class image segmentation using conditional random fields and global classification (NP, MT, SN), pp. 817–824.
ICMLICML-2009-UsunierBG #order #ranking
Ranking with ordered weighted pairwise classification (NU, DB, PG), pp. 1057–1064.
ICMLICML-2009-ZhuAX #modelling #named #topic
MedLDA: maximum margin supervised topic models for regression and classification (JZ, AA, EPX), pp. 1257–1264.
KDDKDD-2009-AmbekarWMMS #open source
Name-ethnicity classification from open sources (AA, CBW, JM, SM, SS), pp. 49–58.
KDDKDD-2009-FormanSR #linear
Feature shaping for linear SVM classifiers (GF, MS, SR), pp. 299–308.
KDDKDD-2009-FrankEK #approach #multi
A multi-relational approach to spatial classification (RF, ME, AJK), pp. 309–318.
KDDKDD-2009-FuxmanKGATS #automation #using
Improving classification accuracy using automatically extracted training data (AF, AK, ABG, RA, PT, JCS), pp. 1145–1154.
KDDKDD-2009-LoCHKS #approach #behaviour #detection #mining
Classification of software behaviors for failure detection: a discriminative pattern mining approach (DL, HC, JH, SCK, CS), pp. 557–566.
KDDKDD-2009-LuoLXZS #case study #information management #towards #web
Towards combining web classification and web information extraction: a case study (PL, FL, YX, YZ, ZS), pp. 1235–1244.
KDDKDD-2009-MelvilleGL #analysis #sentiment
Sentiment analysis of blogs by combining lexical knowledge with text classification (PM, WG, RDL), pp. 1275–1284.
KDDKDD-2009-OzonatY #multi #statistics #towards #web
Towards a universal marketplace over the web: statistical multi-label classification of service provider forms with simulated annealing (KMO, DY), pp. 1295–1304.
KDDKDD-2009-XueW #quantifier
Quantification and semi-supervised classification methods for handling changes in class distribution (JCX, GMW), pp. 897–906.
KDDKDD-2009-YangSWC #effectiveness #learning #multi
Effective multi-label active learning for text classification (BY, JTS, TW, ZC), pp. 917–926.
KDDKDD-2009-YinLMH #graph #social #web
Exploring social tagging graph for web object classification (ZY, RL, QM, JH), pp. 957–966.
KDIRKDIR-2009-BalujaRS #graph #performance
Text Classification through Time — Efficient Label Propagation in Time-Based Graphs (SB, DR, DS), pp. 174–182.
KDIRKDIR-2009-BruyneP
2-class Eigen Transformation Classification Trees (SDB, FP), pp. 251–258.
KDIRKDIR-2009-ClementeDCR #behaviour #image
Behavior of Different Image Classifiers within a Broad Domain (BC, MLD, AC, PGR), pp. 278–283.
KDIRKDIR-2009-GrosserRC
Classification by Successive Neighborhood (DG, HR, NC), pp. 288–291.
KDIRKDIR-2009-VillalbaC #biology #case study #generative #reduction
Artificial Data Generation for One-class Classification — A Case Study of Dimensionality Reduction for Text and Biological Data (SDV, PC), pp. 202–210.
KEODKEOD-2009-ReinekingSH #ontology #statistics
Evidential Combination of Ontological and Statistical Information for Active Scene Classification (TR, NS, JH), pp. 72–79.
MLDMMLDM-2009-DuangsoithongW #analysis
Relevance and Redundancy Analysis for Ensemble Classifiers (RD, TW), pp. 206–220.
MLDMMLDM-2009-GaagRFGEBF #network
Aligning Bayesian Network Classifiers with Medical Contexts (LCvdG, SR, AF, AdG, MJCE, FJB, BCJMF), pp. 787–801.
MLDMMLDM-2009-GoncalvesQ #kernel #semantics #using
Using Graph-Kernels to Represent Semantic Information in Text Classification (TG, PQ), pp. 632–646.
MLDMMLDM-2009-HasanG #adaptation #modelling
Sequential EM for Unsupervised Adaptive Gaussian Mixture Model Based Classifier (BASH, JQG), pp. 96–106.
MLDMMLDM-2009-KobayashiS #distributed #linear #representation #using
A Linear Classification Method in a Very High Dimensional Space Using Distributed Representation (TK, IS), pp. 137–147.
MLDMMLDM-2009-LiuYZZZL #scalability
A Large Margin Classifier with Additional Features (XL, JY, EZ, GZ, YZ, ML), pp. 82–95.
MLDMMLDM-2009-MoedS #performance
Efficient AdaBoost Region Classification (MM, ENS), pp. 123–136.
MLDMMLDM-2009-SilvaSNPJN #geometry #image #metric #using
Lung Nodules Classification in CT Images Using Simpson’s Index, Geometrical Measures and One-Class SVM (CAdS, ACS, SMBN, ACdP, GBJ, RAN), pp. 810–822.
MLDMMLDM-2009-StahlBA #composition #framework #induction #named #parallel
PMCRI: A Parallel Modular Classification Rule Induction Framework (FTS, MAB, MA), pp. 148–162.
MLDMMLDM-2009-WangZ #kernel
Optimal Double-Kernel Combination for Classification (FW, HZ), pp. 107–122.
MLDMMLDM-2009-ZhuFF #privacy
Preserving Privacy in Time Series Data Classification by Discretization (YZ, YF, HF), pp. 53–67.
SEKESEKE-2009-AzizZM #requirements #towards
Towards a Classification of Requirements Relationships (RAA, DZ, TM), pp. 26–32.
SIGIRSIGIR-2009-BennettN #scalability #taxonomy
Refined experts: improving classification in large taxonomies (PNB, NN), pp. 11–18.
SIGIRSIGIR-2009-CaoHSJSCY #query
Context-aware query classification (HC, DHH, DS, DJ, JTS, EC, QY), pp. 3–10.
SIGIRSIGIR-2009-HongD #approach
A classification-based approach to question answering in discussion boards (LH, BDD), pp. 171–178.
SIGIRSIGIR-2009-LiSDZ #sentiment
Knowledge transformation for cross-domain sentiment classification (TL, VS, CHQD, YZ), pp. 716–717.
SIGIRSIGIR-2009-TomasikTT #image #using
Tagging products using image classification (BT, PT, DT), pp. 792–793.
MODELSMoDELS-2009-CuccuruRGT #parametricity #uml
Constraining Type Parameters of UML 2 Templates with Substitutable Classifiers (AC, AR, SG, FT), pp. 644–649.
MODELSMoDELS-2009-CuccuruRGT #parametricity #uml
Constraining Type Parameters of UML 2 Templates with Substitutable Classifiers (AC, AR, SG, FT), pp. 644–649.
TOOLSTOOLS-EUROPE-2009-KloseO #aspect-oriented #framework #monitoring #runtime
A Classification Framework for Pointcut Languages in Runtime Monitoring (KK, KO), pp. 289–307.
RERE-2009-SalinesiRDM #fault #feature model #modelling #product line #towards #verification
Looking for Product Line Feature Models Defects: Towards a Systematic Classification of Verification Criteria (CS, CR, DD, RM), pp. 385–386.
SACSAC-2009-AraujoSSF #named #sequence #type system
HIVSetSubtype: software for subtype classification of HIV-1 sequences (LVdA, SSS, ECS, JEF), pp. 811–815.
SACSAC-2009-BacharM #novel #ranking
A novel distance-based classifier built on pattern ranking (DB, RM), pp. 1427–1432.
SACSAC-2009-BrooksI #detection #novel #visual notation
Visual detection of novel terrain via two-class classification (CAB, KI), pp. 1145–1150.
SACSAC-2009-FalconeFM #monitoring
Enforcement monitoring wrt. the safety-progress classification of properties (YF, JCF, LM), pp. 593–600.
SACSAC-2009-FangLHVAZ #image
Facial image classification of mouse embryos for the animal model study of fetal alcohol syndrome (SF, YL, JH, SVB, BA, FZ), pp. 852–856.
SACSAC-2009-LiuDSYH #algorithm #image #invariant #using
A new K-View algorithm for texture image classification using rotation-invariant feature (HL, SD, ES, CY, CCH), pp. 914–921.
SACSAC-2009-LiuTS #complexity #learning #using
Assessing complexity of service-oriented computing using learning classifier systems (LL, ST, HS), pp. 2170–2171.
SACSAC-2009-PlattMG #detection #topic
Improving classification based off-topic search detection via category relationships (AP, SSRM, NG), pp. 869–874.
SACSAC-2009-ShaLW #using #visual notation
Foreground classification using active template in the scene context for visual surveillance (XS, XL, JW), pp. 943–944.
CASECASE-2009-MakkapatiAA #image #segmentation
Segmentation and classification of tuberculosis bacilli from ZN-stained sputum smear images (VM, RA, RA), pp. 217–220.
CBSECBSE-2008-ParrendF #component #java #platform #programming
Classification of Component Vulnerabilities in Java Service Oriented Programming (SOP) Platforms (PP, SF), pp. 80–96.
DRRDRR-2008-Obafemi-AjayiAF #documentation
Ensemble LUT classification for degraded document enhancement (TOA, GA, OF), p. 681509.
DRRDRR-2008-ReddyG
Form classification (KVUR, VG), p. 68150.
DRRDRR-2008-ZavorinBDBS #recognition #word
Combining different classification approaches to improve off-line Arabic handwritten word recognition (IZ, EB, ED, AB, KMS), p. 681504.
TPDLECDL-2008-PfefferES #analysis #library #visual notation
Visual Analysis of Classification Systems and Library Collections (MP, KE, HS), pp. 436–439.
SIGMODSIGMOD-2008-AndoniFKPS #performance #rank #similarity
Corrigendum to “efficient similarity search and classification via rank aggregation” by Ronald Fagin, Ravi Kumar and D. Sivakumar (proc. SIGMOD’03) (AA, RF, RK, MP, DS), pp. 1375–1376.
SIGMODSIGMOD-2008-PatelHL #mining
Mining relationships among interval-based events for classification (DP, WH, MLL), pp. 393–404.
VLDBVLDB-2008-LeeHLG #clustering #named #using
TraClass: trajectory classification using hierarchical region-based and trajectory-based clustering (JGL, JH, XL, HG), pp. 1081–1094.
EDMEDM-2008-Cho #physics
Machine Classification of Peer Comments in Physics (KC), pp. 192–196.
EDMEDM-2008-LynchAPA #graph #programming #search-based
Argument graph classification with Genetic Programming and C4.5 (CL, KDA, NP, VA), pp. 137–146.
CoGCIG-2008-InoueS #game studies #hybrid #learning #video
Applying GA for reward allotment in an event-driven hybrid learning classifier system for soccer video games (YI, YS), pp. 296–303.
EDOCEDOC-2008-BaglioniBFST #ontology
Ontology-Based Business Plan Classification (MB, AB, BF, LS, FT), pp. 365–371.
ICEISICEIS-AIDSS-2008-AccianiFMM #feature model #search-based #statistics
Genetic Feature Selection and Statistical Classification of Voids in Concrete Structure (GA, GF, DM, DM), pp. 231–234.
ICEISICEIS-AIDSS-2008-StateCRP #algorithm #learning
A New Learning Algorithm for Classification in the Reduced Space (LS, CC, IR, PV), pp. 155–160.
CIKMCIKM-2008-FeiH #feature model #graph
Structure feature selection for graph classification (HF, JH), pp. 991–1000.
CIKMCIKM-2008-Forman #representation #scalability
BNS feature scaling: an improved representation over tf-idf for svm text classification (GF), pp. 263–270.
CIKMCIKM-2008-FormanK #feature model #performance
Extremely fast text feature extraction for classification and indexing (GF, EK), pp. 1221–1230.
CIKMCIKM-2008-HoefelE #learning #sequence
Learning a two-stage SVM/CRF sequence classifier (GH, CE), pp. 271–278.
CIKMCIKM-2008-RochaMPGM
Exploiting temporal contexts in text classification (LCdR, FM, AMP, MAG, WMJ), pp. 243–252.
CIKMCIKM-2008-RosenfeldFU #sequence #using #web
Using sequence classification for filtering web pages (BR, RF, LHU), pp. 1355–1356.
CIKMCIKM-2008-SongZG #framework #performance #process
A sparse gaussian processes classification framework for fast tag suggestions (YS, LZ, CLG), pp. 93–102.
CIKMCIKM-2008-ZhangJYM #effectiveness #retrieval
Improve the effectiveness of the opinion retrieval and opinion polarity classification (WZ, LJ, CTY, WM), pp. 1415–1416.
ECIRECIR-2008-FishbeinE #encoding
Integrating Structure and Meaning: A New Method for Encoding Structure for Text Classification (JMF, CE), pp. 514–521.
ECIRECIR-2008-FishbeinE08a #modelling #semantics
Methods for Augmenting Semantic Models with Structural Information for Text Classification (JMF, CE), pp. 575–579.
ECIRECIR-2008-KritharaARG #documentation #fault
Semi-supervised Document Classification with a Mislabeling Error Model (AK, MRA, JMR, CG), pp. 370–381.
ECIRECIR-2008-WiegandK #modelling #optimisation
Optimizing Language Models for Polarity Classification (MW, DK), pp. 612–616.
ICMLICML-2008-CatanzaroSK #performance
Fast support vector machine training and classification on graphics processors (BCC, NS, KK), pp. 104–111.
ICMLICML-2008-CevikalpTP
Nearest hyperdisk methods for high-dimensional classification (HC, BT, RP), pp. 120–127.
ICMLICML-2008-DredzeCP #linear
Confidence-weighted linear classification (MD, KC, FP), pp. 264–271.
ICMLICML-2008-DundarWLSR #case study #detection
Polyhedral classifier for target detection: a case study: colorectal cancer (MD, MW, SL, MS, VCR), pp. 288–295.
ICMLICML-2008-LarochelleB #strict #using
Classification using discriminative restricted Boltzmann machines (HL, YB), pp. 536–543.
ICMLICML-2008-LiLT #constraints #programming
Pairwise constraint propagation by semidefinite programming for semi-supervised classification (ZL, JL, XT), pp. 576–583.
ICMLICML-2008-LongS #random
Random classification noise defeats all convex potential boosters (PML, RAS), pp. 608–615.
ICMLICML-2008-Nijssen
Bayes optimal classification for decision trees (SN), pp. 696–703.
ICMLICML-2008-OBrienGG #multi #probability
Cost-sensitive multi-class classification from probability estimates (DBO, MRG, RMG), pp. 712–719.
ICMLICML-2008-PalatucciC #on the #scalability
On the chance accuracies of large collections of classifiers (MP, AC), pp. 744–751.
ICMLICML-2008-SeldinT #category theory #clustering #multi
Multi-classification by categorical features via clustering (YS, NT), pp. 920–927.
ICMLICML-2008-SriperumbudurLL #kernel #metric
Metric embedding for kernel classification rules (BKS, OAL, GRGL), pp. 1008–1015.
ICPRICPR-2008-Abd-AlmageedASD #hybrid #using
Document-zone classification using partial least squares and hybrid classifiers (WAA, MA, WS, DSD), pp. 1–4.
ICPRICPR-2008-AdankonC
Help-training for semi-supervised discriminative classifiers. Application to SVM (MMA, MC), pp. 1–4.
ICPRICPR-2008-Bauckhage #detection #probability
Probabilistic Diffusion Classifiers for Object Detection (CB), pp. 1–4.
ICPRICPR-2008-CaoBLLH #word
Audio-visual event classification via spatial-temporal-audio words (YC, SB, SHL, ML, SH), pp. 1–5.
ICPRICPR-2008-ChenTZ #novel
Spam filtering with several novel bayesian classifiers (CC, YT, CZ), pp. 1–4.
ICPRICPR-2008-ChouaibTTCV #algorithm #feature model #search-based
Feature selection combining genetic algorithm and Adaboost classifiers (HC, ORT, ST, FC, NV), pp. 1–4.
ICPRICPR-2008-Dahyot #statistics
Bayesian classification for the Statistical Hough transform (RD), pp. 1–4.
ICPRICPR-2008-DehzangiMCL #fuzzy #learning #speech #using
Fuzzy rule selection using Iterative Rule Learning for speech data classification (OD, BM, CES, HL), pp. 1–4.
ICPRICPR-2008-DeselaersPN #image #modelling
Bag-of-visual-words models for adult image classification and filtering (TD, LP, HN), pp. 1–4.
ICPRICPR-2008-EskofierHK
Classification of perceived running fatigue in digital sports (BE, FH, PK), pp. 1–4.
ICPRICPR-2008-GamboaF #nondeterminism #testing
Uncertainty based classification fusion — a soft-biometrics test case (HG, ALNF), pp. 1–4.
ICPRICPR-2008-GaoL #polynomial #recognition
Combining quadratic classifier and pair discriminators by pairwise coupling for handwritten Chinese character recognition (TFG, CLL), pp. 1–4.
ICPRICPR-2008-GeorgeKK #hybrid
Hybrid wavelet support vector classification of temporal bone abnormalities (JG, STK, RK), pp. 1–4.
ICPRICPR-2008-GhoshM #documentation #kernel #similarity #using #xml
Combining content and structure similarity for XML document classification using composite SVM kernels (SG, PM), pp. 1–4.
ICPRICPR-2008-GuehamBC #automation #correlation #forensics #using
Automatic classification of partial shoeprints using Advanced Correlation Filters for use in forensic science (MG, AB, DC), pp. 1–4.
ICPRICPR-2008-GuoFDH #estimation #question
Head pose estimation: Classification or regression? (GG, YF, CRD, TSH), pp. 1–4.
ICPRICPR-2008-HadidP #gender #sequence #video
Combining motion and appearance for gender classification from video sequences (AH, MP), pp. 1–4.
ICPRICPR-2008-Hernandez-RodriguezTC #on the #prototype
On the selection of base prototypes for LAESA and TLAESA classifiers (SHR, JFMT, JACO), pp. 1–4.
ICPRICPR-2008-KarnickMP #approach #concept #incremental #learning #multi #using
Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach (MTK, MM, RP), pp. 1–4.
ICPRICPR-2008-KokiopoulouPF #graph #multi
Graph-based classification for multiple observations of transformed patterns (EK, SP, PF), pp. 1–4.
ICPRICPR-2008-KottiK #database #gender #speech
Gender classification in two Emotional Speech databases (MK, CK), pp. 1–4.
ICPRICPR-2008-LiuJ #multi
Violence classification based on shape variations from multiple views (FL, YJ), pp. 1–4.
ICPRICPR-2008-LuFJW #framework #learning #metric #reduction #visualisation
Metric Learning: A general dimension reduction framework for classification and visualization (CL, GF, JJ, PSPW), pp. 1–4.
ICPRICPR-2008-MunizCR #independence #using
Use of band ratioing for building illumination independent texture classification systems (RM, JAC, MRS), pp. 1–4.
ICPRICPR-2008-PesarinCMDPT #automation #statistics
A statistical signature for automatic dialogue classification (AP, MC, VM, CD, AP, AT), pp. 1–4.
ICPRICPR-2008-PiccardiGO #modelling #reduction
Maximum-likelihood dimensionality reduction in gaussian mixture models with an application to object classification (MP, HG, AFO), pp. 1–4.
ICPRICPR-2008-RavesteijnVSTV
Thin layer tissue classification for electronic cleansing of CT colonography data (VFvR, FMV, IS, RT, LJvV), pp. 1–5.
ICPRICPR-2008-RysavyFEO #random #segmentation
Classifiability criteria for refining of random walks segmentation (SR, AF, RE, KO), pp. 1–4.
ICPRICPR-2008-Sakai #approach #incremental #monte carlo
Monte Carlo subspace method: An incremental approach to high-dimensional data classification (TS), pp. 1–4.
ICPRICPR-2008-ScalzoBNLT #gender
Feature Fusion Hierarchies for gender classification (FS, GB, MN, LAL, AT), pp. 1–4.
ICPRICPR-2008-SeiffertKHN #named #performance
RUSBoost: Improving classification performance when training data is skewed (CS, TMK, JVH, AN), pp. 1–4.
ICPRICPR-2008-SerCY #hybrid #recognition #speech
A Hybrid PNN-GMM classification scheme for speech emotion recognition (WS, LC, ZLY), pp. 1–4.
ICPRICPR-2008-SharmaCS #kernel
Bag-of-features kernel eigen spaces for classification (GS, SC, JBS), pp. 1–4.
ICPRICPR-2008-ShidaraKN #consistency
Classification by bagged consistent itemset rules (YS, MK, AN), pp. 1–4.
ICPRICPR-2008-SongT
C1 units for scene classification (DS, DT), pp. 1–4.
ICPRICPR-2008-SunQ #network
Dynamic target classification in wireless sensor networks (YS, HQ), pp. 1–4.
ICPRICPR-2008-TarghiGZ #image
Texture classification with minimal training images (ATT, JMG, AZ), pp. 1–4.
ICPRICPR-2008-TeynorB
Wavelet-based salient points with scale information for classification (AT, HB), pp. 1–5.
ICPRICPR-2008-TominagaY
Metal-dielectric object classification by polarization degree map (ST, TY), pp. 1–4.
ICPRICPR-2008-UchidaA #recognition
Early recognition of sequential patterns by classifier combination (SU, KA), pp. 1–4.
ICPRICPR-2008-VillS #analysis #automation
Automated stroke ending analysis for drawing tool classification (MCV, RS), pp. 1–4.
ICPRICPR-2008-WangC #semantics #using
Film shot classification using directing semantics (HLW, LFC), pp. 1–4.
ICPRICPR-2008-WangI #image #markov #modelling #multi #semantics
Combining multiple spatial hidden Markov models in image semantic classification and annotation (LW, HHSI), pp. 1–4.
ICPRICPR-2008-WimmerHS #bound
Implicit active shape model employing boundary classifier (AW, JH, GS), pp. 1–4.
ICPRICPR-2008-WuF #3d #learning #multi #using
Multiple view based 3D object classification using ensemble learning of local subspaces (JW, KF), pp. 1–4.
ICPRICPR-2008-WuSH #gender
Gender classification based on facial surface normals (JW, WAPS, ERH), pp. 1–4.
ICPRICPR-2008-YamaguchiM #categorisation #image #probability #topic
Image categorization by a classifier based on probabilistic topic model (TY, MM), pp. 1–4.
ICPRICPR-2008-YarlagaddaOM #3d #distance
Lie group distance based generic 3-d vehicle classification (PY, ÖCÖ, JLM), pp. 1–4.
ICPRICPR-2008-YuS #visual notation
FastWavelet-Based Visual Classification (GY, JJES), pp. 1–5.
ICPRICPR-2008-YuW #3d #clustering #knowledge base
Knowledge based cluster ensemble for 3D head model classification (ZY, HSW), pp. 1–4.
ICPRICPR-2008-ZhangLHT #automation
Boosting local feature descriptors for automatic objects classification in traffic scene surveillance (ZZ, ML, KH, TT), pp. 1–4.
ICPRICPR-2008-ZhongGA #algorithm
Properties of the k-norm pruning algorithm for decision tree classifiers (MZ, MG, GCA), pp. 1–4.
ICPRICPR-2008-ZhouWS #process #recognition #using
Human motion recognition using Gaussian Processes classification (HZ, LW, DS), pp. 1–4.
KDDKDD-2008-BilgicG #effectiveness
Effective label acquisition for collective classification (MB, LG), pp. 43–51.
KDDKDD-2008-ChenJCLWY #kernel #learning
Learning subspace kernels for classification (JC, SJ, BC, QL, MW, JY), pp. 106–114.
KDDKDD-2008-ChenW #feature model #metric #named #performance #problem
FAST: a roc-based feature selection metric for small samples and imbalanced data classification problems (XwC, MW), pp. 124–132.
KDDKDD-2008-Christen #automation #nearest neighbour #using
Automatic record linkage using seeded nearest neighbour and support vector machine classification (PC), pp. 151–159.
KDDKDD-2008-ElkanN #learning
Learning classifiers from only positive and unlabeled data (CE, KN), pp. 213–220.
KDDKDD-2008-FormanR #file system #scalability
Scaling up text classification for large file systems (GF, SR), pp. 239–246.
KDDKDD-2008-GallagherTEF #network #using
Using ghost edges for classification in sparsely labeled networks (BG, HT, TER, CF), pp. 256–264.
KDDKDD-2008-GodboleR #analysis #automation #industrial
Text classification, business intelligence, and interactivity: automating C-Sat analysis for services industry (SG, SR), pp. 911–919.
KDDKDD-2008-JiTYY #multi
Extracting shared subspace for multi-label classification (SJ, LT, SY, JY), pp. 381–389.
KDDKDD-2008-NguyenC
Classification with partial labels (NN, RC), pp. 551–559.
KDDKDD-2008-SunJY #learning #multi
Hypergraph spectral learning for multi-label classification (LS, SJ, JY), pp. 668–676.
KDDKDD-2008-WangD #kernel #semantics #using #wiki
Building semantic kernels for text classification using wikipedia (PW, CD), pp. 713–721.
SEKESEKE-2008-Chao #data type #privacy
Privacy-preserving Classification of Data Streams (CMC), pp. 603–606.
SEKESEKE-2008-FollecoKB #quality
Analyzing the Impact of Attribute Noise on Software Quality Classification (AF, TMK, LAB), pp. 73–78.
SEKESEKE-2008-LucasSM #personalisation #recommendation #towards #using
Comparing the Use of Traditional and Associative Classifiers towards Personalized Recommendations (JPL, SS, MNMG), pp. 607–612.
SIGIRSIGIR-2008-Banerjee #corpus #modelling #topic #using
Improving text classification accuracy using topic modeling over an additional corpus (SB), pp. 867–868.
SIGIRSIGIR-2008-CrainHZ #scalability
A scalable assistant librarian: hierarchical subject classification of books (SPC, JH, HZ), pp. 799–800.
SIGIRSIGIR-2008-ElgersmaR
Personal vs non-personal blogs: initial classification experiments (EE, MdR), pp. 723–724.
SIGIRSIGIR-2008-PanTLL #kernel #semantics
Question classification with semantic tree kernel (YP, YT, LL, YL), pp. 837–838.
SIGIRSIGIR-2008-QiD #web
Classifiers without borders: incorporating fielded text from neighboring web pages (XQ, BDD), pp. 643–650.
SIGIRSIGIR-2008-WestDHJ #music #visualisation
Dynamic visualization of music classification systems (KW, JSD, XH, MCJ), p. 888.
SIGIRSIGIR-2008-WuO #topic
Bilingual topic aspect classification with a few training examples (YW, DWO), pp. 203–210.
SIGIRSIGIR-2008-XueDYY #topic
Topic-bridged PLSA for cross-domain text classification (GRX, WD, QY, YY), pp. 627–634.
SIGIRSIGIR-2008-XueXYY #scalability
Deep classification in large-scale text hierarchies (GRX, DX, QY, YY), pp. 619–626.
ECMFAECMDA-FA-2008-GoldschmidtBU #syntax
Classification of Concrete Textual Syntax Mapping Approaches (TG, SB, AU), pp. 169–184.
SACSAC-2008-BechiniTV #documentation #ontology
Enabling ontology-based document classification and management in ebXML registries (AB, AT, JV), pp. 1145–1150.
SACSAC-2008-ChenC #web
Web page genre classification (GC, BC), pp. 2353–2357.
SACSAC-2008-HanaFOB
Crime scene classification (ROAH, COdAF, LSO, FB), pp. 419–423.
SACSAC-2008-Hassan #automation #open source
Automated classification of change messages in open source projects (AEH), pp. 837–841.
SACSAC-2008-LucasCD #fuzzy
General type-2 fuzzy classifiers to land cover classification (LAL, TMC, MRD), pp. 1743–1747.
SACSAC-2008-MengleG #algorithm #ambiguity #feature model #using
Using ambiguity measure feature selection algorithm for support vector machine classifier (SSRM, NG), pp. 916–920.
SACSAC-2008-MengleGP #category theory #using
Discovering relationships among categories using misclassification information (SSRM, NG, AP), pp. 932–937.
SACSAC-2008-NhatL #visualisation
k-means discriminant maps for data visualization and classification (VDMN, SL), pp. 1187–1191.
SACSAC-2008-NollM #documentation #social #web
Exploring social annotations for web document classification (MGN, CM), pp. 2315–2320.
SACSAC-2008-RadtkeSW #algorithm #using
Using the RRT algorithm to optimize classification systems for handwritten digits and letters (PVWR, RS, TW), pp. 1748–1752.
SACSAC-2008-ShaoYN
Strangeness-based feature weighting and classification of gene expression profiles (HS, BY, JHN), pp. 1292–1296.
SACSAC-2008-SuKZG #collaboration #machine learning #using
Imputation-boosted collaborative filtering using machine learning classifiers (XS, TMK, XZ, RG), pp. 949–950.
PDPPDP-2008-HoferF #fault #grid #multi #taxonomy
A Multi-Perspective Taxonomy for Systematic Classification of Grid Faults (JH, TF), pp. 126–130.
PPoPPPPoPP-2008-ChengCHT #manycore #platform #scalability #using
Scalable packet classification using interpreting: a cross-platform multi-core solution (HC, ZC, BH, XT), pp. 33–42.
ESOPESOP-2008-KanekoK #linear
Linear Declassification (YK, NK), pp. 224–238.
DocEngDocEng-2007-LiSGR #adaptation #categorisation
Adapting associative classification to text categorization (BL, NS, EVG, AR), pp. 205–208.
DRRDRR-2007-JoutelEBE #feature model
Curvelets based feature extraction of handwritten shapes for ancient manuscripts classification (GJ, VE, SB, HE).
TPDLECDL-2007-GiunchigliaZK #algorithm #documentation #formal method
Formalizing the Get-Specific Document Classification Algorithm (FG, IZ, UK), pp. 26–37.
HTHT-2007-LeveringCY #html #visual notation
Visual features in genre classification of html (RL, MC, LY), pp. 51–52.
HTHT-2007-WuZM #collaboration #evolution
Collaborative classification of growing collections with evolving facets (HW, MZ, KM), pp. 167–170.
ICDARICDAR-2007-Al-HajjML #recognition #word
Combination of HMM-Based Classifiers for the Recognition of Arabic Handwritten Words (RAHM, CM, LLS), pp. 959–963.
ICDARICDAR-2007-AnBX #documentation
Iterated Document Content Classification (CA, HSB, PX), pp. 252–256.
ICDARICDAR-2007-ChouGC #multi #recognition #using
Recognition of Fragmented Characters Using Multiple Feature-Subset Classifiers (CHC, CYG, FC), pp. 198–202.
ICDARICDAR-2007-Dengel #documentation #learning
Learning of Pattern-Based Rules for Document Classification (AD), pp. 123–127.
ICDARICDAR-2007-FuDLL #effectiveness #recognition
An Effective and Practical Classifier Fusion Strategy for Improving Handwritten Character Recognition (QF, XD, TL, CL), pp. 1038–1042.
ICDARICDAR-2007-HirayamaNK #difference #using
A Classifier of Similar Characters using Compound Mahalanobis Function based on Difference Subspace (JH, HN, NK), pp. 432–436.
ICDARICDAR-2007-Hotta #pattern matching #pattern recognition #recognition
Transform-Invariance in Local Averaging Classifier for Handwritten Digit Pattern Recognition (SH), pp. 347–351.
ICDARICDAR-2007-KalvaEK #image #web
WEB Image Classification Based on the Fusion of Image and Text Classifiers (PRK, FE, ALK), pp. 561–568.
ICDARICDAR-2007-LongJ
Building Compact MQDF Classifier for Off-line Handwritten Chinese Characters by Subspace Distribution Sharing (TL, LJ), pp. 909–913.
ICDARICDAR-2007-NguyenBML #using #verification
Off-line Signature Verification Using Enhanced Modified Direction Features in Conjunction with Neural Classifiers and Support Vector Machines (VN, MB, VM, GL), pp. 734–738.
ICDARICDAR-2007-SilvaN #markov #modelling #performance #visualisation
A Visualization Tool to Improve the Performance of a Classifier Based on Hidden Markov Models (GdS, MN), pp. 1083–1087.
ICDARICDAR-2007-SundaramR #novel #online #recognition
A Novel Hierarchical Classification Scheme for Online Tamil Character Recognition (SS, AR), pp. 1218–1222.
ICDARICDAR-2007-SunHHFN #recognition
Degraded Character Recognition by Complementary Classifiers Combination (JS, KH, YH, KF, SN), pp. 579–583.
ICDARICDAR-2007-ZhouLQA #markov #random
Text/Non-text Ink Stroke Classification in Japanese Handwriting Based on Markov Random Fields (XDZ, CLL, SQ, ÉA), pp. 377–381.
JCDLJCDL-2007-KeMF #collaboration #distributed #documentation #learning
Collaborative classifier agents: studying the impact of learning in distributed document classification (WK, JM, YF), pp. 428–437.
JCDLJCDL-2007-LiCZL #automation #case study #network #using
Automatic patent classification using citation network information: an experimental study in nanotechnology (XL, HC, ZZ, JL), pp. 419–427.
JCDLJCDL-2007-YuTFPFCTC #automation
Automatic syllabus classification (XY, MT, WF, MAPQ, EAF, WC, GT, LNC), pp. 440–441.
ICSMEICSM-2007-LuccaFT #concept analysis #using #web
Web Pages Classification using Concept Analysis (GADL, ARF, PT), pp. 385–394.
LISPILC-2007-Borden #using
Classification using conditional probabilities and Shannon’s definition of information (AB), p. 15.
CoGCIG-2007-AkatsukaS #game studies #learning #video
Reward Allotment Considered Roles for Learning Classifier System For Soccer Video Games (YA, YS), pp. 288–295.
DiGRADiGRA-2007-Leino #game studies #sketching
Emotions about the Deniable/Undeniable: Sketch for a Classification of Game Content as Experienced (OTL).
HCIDHM-2007-WangYHWJJLZ #hybrid
A Hybrid AB-RBF Classifier for Surface Electromyography Classification (RW, YY, XH, FW, DJ, XJ, FL, JZ), pp. 727–735.
HCIHCI-AS-2007-LiYG #network #realtime #towards
Traffic Classification — Towards Accurate Real Time Network Applications (ZL, RY, XG), pp. 67–76.
HCIHCI-IPT-2007-LiuS #interactive #visual notation
Interactive Visual Decision Tree Classification (YL, GS), pp. 92–105.
HCIHCI-MIE-2007-ChungK #using
Classification of a Person Picture and Scenery Picture Using Structured Simplicity (MBC, IJK), pp. 821–828.
HCIHCI-MIE-2007-HilligesKPBK #analysis #automation #image #quality #sorting #using
Browsing and Sorting Digital Pictures Using Automatic Image Classification and Quality Analysis (OH, PK, AP, AB, HPK), pp. 882–891.
HCIHCI-MIE-2007-Shirehjini #interactive #multi
A Multidimensional Classification Model for the Interaction in Reactive Media Rooms (AANS), pp. 431–439.
HCIHIMI-MTT-2007-MarucciLC #approach #fuzzy #using
Computer Classification of Injury Narratives Using a Fuzzy Bayes Approach: Improving the Model (HRM, MRL, HLC), pp. 500–506.
HCIHIMI-MTT-2007-NoorinaeiniLW #composition #hybrid
Hybrid Singular Value Decomposition: A Model of Human Text Classification (AN, MRL, SjW), pp. 517–525.
HCIOCSC-2007-CarcilloR #bottom-up #top-down
Tags for Citizens: Integrating Top-Down and Bottom-Up Classification in the Turin Municipality Website (FC, LR), pp. 256–264.
EDOCEDOC-2007-Dijkman #difference
A Classification of Differences between Similar BusinessProcesses (RMD), pp. 37–50.
ICEISICEIS-AIDSS-2007-KrohaR #using
Using Grammars for Text Classification (PK, TR), pp. 259–264.
ICEISICEIS-AIDSS-2007-StateCPS #approach
A Connectionist Approach in Bayesian Classification (LS, CC, PV, VS), pp. 185–190.
CIKMCIKM-2007-ErtekinHBG #learning
Learning on the border: active learning in imbalanced data classification (SE, JH, LB, CLG), pp. 127–136.
CIKMCIKM-2007-FortunaRM #analysis #network #social
Improving the classification of newsgroup messages through social network analysis (BF, EMR, NMF), pp. 877–880.
CIKMCIKM-2007-JiangZ #adaptation #approach #statistics
A two-stage approach to domain adaptation for statistical classifiers (JJ, CZ), pp. 401–410.
CIKMCIKM-2007-WangL #interactive
Reconstructing ddc for interactive classification (JW, MCL), pp. 137–146.
CIKMCIKM-2007-ZhangLYSLM #effectiveness #query #recognition #retrieval
Recognition and classification of noun phrases in queries for effective retrieval (WZ, SL, CTY, CS, FL, WM), pp. 711–720.
ECIRECIR-2007-AyacheQG #multi #semantics
Classifier Fusion for SVM-Based Multimedia Semantic Indexing (SA, GQ, JG), pp. 494–504.
ECIRECIR-2007-BettsMO #information management
The Utility of Information Extraction in the Classification of Books (TB, MM, JO), pp. 295–306.
ECIRECIR-2007-BloehdornM #kernel #semantics
Combined Syntactic and Semantic Kernels for Text Classification (SB, AM), pp. 307–318.
ECIRECIR-2007-HeD #naive bayes #using
Improving Naive Bayes Text Classifier Using Smoothing Methods (FH, XD), pp. 703–707.
ECIRECIR-2007-MeloS #multi #ontology #using
Multilingual Text Classification Using Ontologies (GdM, SS), pp. 541–548.
ECIRECIR-2007-MerkelK #modelling #query
Language Model Based Query Classification (AM, DK), pp. 720–723.
ECIRECIR-2007-NeumayerR #information retrieval #integration #music
Integration of Text and Audio Features for Genre Classification in Music Information Retrieval (RN, AR), pp. 724–727.
ECIRECIR-2007-QuarteroniMMB #ranking
Advanced Structural Representations for Question Classification and Answer Re-ranking (SQ, AM, SM, RB), pp. 234–245.
ICMLICML-2007-AmitFSU #multi
Uncovering shared structures in multiclass classification (YA, MF, NS, SU), pp. 17–24.
ICMLICML-2007-BhattacharyaBC #kernel
Structural alignment based kernels for protein structure classification (SB, CB, NRC), pp. 73–80.
ICMLICML-2007-ChenJ #feature model #set
Minimum reference set based feature selection for small sample classifications (XwC, JCJ), pp. 153–160.
ICMLICML-2007-EspositoR #algorithm #evaluation #named #performance
CarpeDiem: an algorithm for the fast evaluation of SSL classifiers (RE, DPR), pp. 257–264.
ICMLICML-2007-HeraultG #probability
Sparse probabilistic classifiers (RH, YG), pp. 337–344.
ICMLICML-2007-LiaoLC #semistructured data
Quadratically gated mixture of experts for incomplete data classification (XL, HL, LC), pp. 553–560.
ICMLICML-2007-UrtasunD #process
Discriminative Gaussian process latent variable model for classification (RU, TD), pp. 927–934.
ICMLICML-2007-WangZZ #array #hybrid
Hybrid huberized support vector machines for microarray classification (LW, JZ, HZ), pp. 983–990.
ICMLICML-2007-ZhangXSGL #metric
Optimal dimensionality of metric space for classification (WZ, XX, ZS, YFG, HL), pp. 1135–1142.
ICMLICML-2007-ZhangY #consistency #constraints #on the
On the value of pairwise constraints in classification and consistency (JZ, RY), pp. 1111–1118.
KDDKDD-2007-Aggarwal #data type #framework #segmentation
A framework for classification and segmentation of massive audio data streams (CCA), pp. 1013–1017.
KDDKDD-2007-AggarwalY #data type #on the #string
On string classification in data streams (CCA, PSY), pp. 36–45.
KDDKDD-2007-ChaovalitwongseFS #process
Support feature machine for classification of abnormal brain activity (WAC, YJF, RCS), pp. 113–122.
KDDKDD-2007-DaiXYY #clustering #documentation
Co-clustering based classification for out-of-domain documents (WD, GRX, QY, YY), pp. 210–219.
KDDKDD-2007-DasguptaDHJM #feature model
Feature selection methods for text classification (AD, PD, BH, VJ, MWM), pp. 230–239.
KDDKDD-2007-DruckPMZ #generative #hybrid
Semi-supervised classification with hybrid generative/discriminative methods (GD, CP, AM, XZ), pp. 280–289.
KDDKDD-2007-KolczY
Raising the baseline for high-precision text classifiers (AK, WtY), pp. 400–409.
KDDKDD-2007-LuoXLS #distributed #network #peer-to-peer
Distributed classification in peer-to-peer networks (PL, HX, KL, ZS), pp. 968–976.
KDDKDD-2007-SmithE #bias #generative #robust
Making generative classifiers robust to selection bias (ATS, CE), pp. 657–666.
KDDKDD-2007-YanTS #multi
Model-shared subspace boosting for multi-label classification (RY, JT, JRS), pp. 834–843.
MLDMMLDM-2007-CoenenLSW #identification #statistics
Statistical Identification of Key Phrases for Text Classification (FC, PHL, RS, YJW), pp. 838–853.
MLDMMLDM-2007-EkdahlK #learning #on the
On Concentration of Discrete Distributions with Applications to Supervised Learning of Classifiers (ME, TK), pp. 2–16.
MLDMMLDM-2007-Kertesz-FarkasKP #equivalence #learning
Equivalence Learning in Protein Classification (AKF, AK, SP), pp. 824–837.
MLDMMLDM-2007-MartinsSSPG #image #using
Classification of Breast Masses in Mammogram Images Using Ripley’s K Function and Support Vector Machine (LdOM, ECdS, ACS, ACdP, MG), pp. 784–794.
MLDMMLDM-2007-ShidaraNK #consistency #named
CCIC: Consistent Common Itemsets Classifier (YS, AN, MK), pp. 490–498.
MLDMMLDM-2007-SzepannekBW #on the
On the Combination of Locally Optimal Pairwise Classifiers (GS, BB, CW), pp. 104–116.
MLDMMLDM-2007-WangLYC #data type #fuzzy #incremental #mining
An Incremental Fuzzy Decision Tree Classification Method for Mining Data Streams (TW, ZL, YY, HC), pp. 91–103.
MLDMMLDM-2007-WangXC #approach #mining #novel
A Novel Rule Ordering Approach in Classification Association Rule Mining (YJW, QX, FC), pp. 339–348.
MLDMMLDM-2007-YuL #approach #graph #named
PE-PUC: A Graph Based PU-Learning Approach for Text Classification (SY, CL), pp. 574–584.
RecSysRecSys-2007-PronkVPT #naive bayes #recommendation
Incorporating user control into recommender systems based on naive bayesian classification (VP, WFJV, AP, MT), pp. 73–80.
SEKESEKE-2007-AlencarRSF #modelling #probability #project management
Combining Decorated Classification Trees with RCPS Stochastic Models to Gain New Valuable Insights into Software Project Management (AJA, GGR, EAS, ALF), pp. 151–156.
SEKESEKE-2007-CordeiroGES #constraints #database #design #version control
A Deep Classification of Temporal Versioned Integrity Constraints for Designing Database Applications (RLFC, RdMG, NE, CSdS), pp. 416–421.
SEKESEKE-2007-DongZ #design pattern
Classification of Design Pattern Traits (JD, YZ), p. 473–?.
SEKESEKE-2007-LiZXS #component #generative #ontology #retrieval
Ontology Based Classification Generating Method for Browsing-Based Component Retrieval (GL, LZ, BX, WS), p. 428–?.
SIGIRSIGIR-2007-BeitzelJCF #query #topic #web
Varying approaches to topical web query classification (SMB, ECJ, AC, OF), pp. 783–784.
SIGIRSIGIR-2007-BroderFGJJZ #query #robust #using #web
Robust classification of rare queries using web knowledge (AZB, MF, EG, AJ, VJ, TZ), pp. 231–238.
SIGIRSIGIR-2007-FanGL #automation #image
Hierarchical classification for automatic image annotation (JF, YG, HL), pp. 111–118.
SIGIRSIGIR-2007-HuDGX #documentation #locality
Locality discriminating indexing for document classification (JH, WD, JG, WX), pp. 689–690.
SIGIRSIGIR-2007-KyriakopoulouK #clustering #using
Using clustering to enhance text classification (AK, TK), pp. 805–806.
SIGIRSIGIR-2007-OlssonO
Improving text classification for oral history archives with temporal domain knowledge (JSO, DWO), pp. 623–630.
SIGIRSIGIR-2007-StaffB #automation #category theory #web
Automatic classification of web pages into bookmark categories (CS, IB), pp. 731–732.
SIGIRSIGIR-2007-StepinskiM
A fact/opinion classifier for news articles (AS, VOM), pp. 807–808.
SIGIRSIGIR-2007-ZhangL #semantics
Semantic text classification of disease reporting (YZ, BL), pp. 747–748.
SIGIRSIGIR-2007-ZhuYCG #matrix #using
Combining content and link for classification using matrix factorization (SZ, KY, YC, YG), pp. 487–494.
SACSAC-2007-Cardoso-CachopoO #categorisation #using
Semi-supervised single-label text categorization using centroid-based classifiers (ACC, ALO), pp. 844–851.
SACSAC-2007-LeeOSYT #automation
Automatic classification of digestive organs in wireless capsule endoscopy videos (JL, JHO, SKS, XY, SJT), pp. 1041–1045.
SACSAC-2007-TanC #using
Using hypothesis margin to boost centroid text classifier (ST, XC), pp. 398–403.
SACSAC-2007-VanderleiDMGAM #component #retrieval
A cooperative classification mechanism for search and retrieval software components (TAV, FAD, ACM, VCG, ESdA, SRdLM), pp. 866–871.
SACSAC-2007-XiongCL #database #mining #multi #using
Mining multiple private databases using a kNN classifier (LX, SC, LL), pp. 435–440.
SACSAC-2007-ZengWN #analysis
Text classification based on partial least square analysis (XQZ, MWW, JYN), pp. 834–838.
CASECASE-2007-ChenT #gesture #multi #recognition
Multiple-angle Hand Gesture Recognition by Fusing SVM Classifiers (YTC, KTT), pp. 527–530.
CASECASE-2007-McVittieSMMLHM #automation #using
Automated Classification of Macrophage Membrane Integrity using a Fluorescent Live/Dead Stain (PM, CSS, TWM, SM, MEL, MH, DRM), pp. 554–559.
DATEDATE-2007-NarayananHMCZ #implementation #interactive
Interactive presentation: An FPGA implementation of decision tree classification (RN, DH, GM, ANC, JZ), pp. 189–194.
ESOPESOP-2007-MantelR #security #what
Controlling the What and Where of Declassification in Language-Based Security (HM, AR), pp. 141–156.
DocEngDocEng-2006-SimskeWS #documentation
Meta-algorithmic systems for document classification (SJS, DWW, MS), pp. 98–106.
DRRDRR-2006-AndraZ #consistency #nearest neighbour
Style consistent nearest neighbor classifier (SA, XZ).
DRRDRR-2006-AsSadhanBSN #comparative #evaluation #recognition #robust
Comparative evaluation of different classifiers for robust distorted-character recognition (BA, ZAB, AES, MN).
DRRDRR-2006-ChellapillaSS
Optimally combining a cascade of classifiers (KC, MS, PYS).
TPDLECDL-2006-GolubAMG #automation
Comparing and Combining Two Approaches to Automated Subject Classification of Text (KG, AA, DM, MG), pp. 467–470.
TPDLECDL-2006-KimR #automation #metadata
Genre Classification in Automated Ingest and Appraisal Metadata (YK, SR), pp. 63–74.
JCDLJCDL-2006-CoutoCGCZMR #case study #comparative #documentation
A comparative study of citations and links in document classification (TC, MC, MAG, PC, NZ, ESdM, BARN), pp. 75–84.
SCAMSCAM-2006-PanKW #debugging #metric #slicing #using
Bug Classification Using Program Slicing Metrics (KP, SK, EJWJ), pp. 31–42.
ICEISICEIS-J-2006-Leukel06a #approach #data transformation
Controlling Property Growth in Product Classification Schemes: A Data Management Approach (JL), pp. 363–374.
ICEISICEIS-SAIC-2006-Leukel #library #maintenance
Maintaining Property Libraries in Product Classification Schemes (JL), pp. 3–10.
CIKMCIKM-2006-AnagnostopoulosBP #effectiveness #performance
Effective and efficient classification on a search-engine model (AA, AZB, KP), pp. 208–217.
CIKMCIKM-2006-AssfalgBK #3d #kernel #named #string
3DString: a feature string kernel for 3D object classification on voxelized data (JA, KMB, HPK), pp. 198–207.
CIKMCIKM-2006-OlssonO
Combining feature selectors for text classification (JSO, DWO), pp. 798–799.
CIKMCIKM-2006-SchutzeVP #performance
Performance thresholding in practical text classification (HS, EV, JOP), pp. 662–671.
CIKMCIKM-2006-ShenSYC #modelling #multi
Text classification improved through multigram models (DS, JTS, QY, ZC), pp. 672–681.
CIKMCIKM-2006-VelosoMCGZ #documentation #lazy evaluation #multi
Multi-evidence, multi-criteria, lazy associative document classification (AV, WMJ, MC, MAG, MJZ), pp. 218–227.
CIKMCIKM-2006-XiongCL #database #multi #nearest neighbour
k nearest neighbor classification across multiple private databases (LX, SC, LL), pp. 840–841.
CIKMCIKM-2006-XuWFSP #correlation #data type
Classification spanning correlated data streams (YX, KW, AWCF, RS, JP), pp. 132–141.
ECIRECIR-2006-BoumaR
Specificity Helps Text Classification (LB, MdR), pp. 539–542.
ECIRECIR-2006-DemartiniM #effectiveness #information retrieval #metric
A Classification of IR Effectiveness Metrics (GD, SM), pp. 488–491.
ECIRECIR-2006-KeBO #email #named
PERC: A Personal Email Classifier (SWK, CB, MPO), pp. 460–463.
ECIRECIR-2006-YinP #adaptation #naive bayes #rank
Adapting the Naive Bayes Classifier to Rank Procedural Texts (LY, RP), pp. 179–190.
ICMLICML-2006-Cesa-BianchiGZ
Hierarchical classification: combining Bayes with SVM (NCB, CG, LZ), pp. 177–184.
ICMLICML-2006-DaiYTK #adaptation #nondeterminism
Locally adaptive classification piloted by uncertainty (JD, SY, XT, JTK), pp. 225–232.
ICMLICML-2006-DenisMR #learning #naive bayes #performance
Efficient learning of Naive Bayes classifiers under class-conditional classification noise (FD, CNM, LR), pp. 265–272.
ICMLICML-2006-GravesFGS #network #sequence
Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks (AG, SF, FJG, JS), pp. 369–376.
ICMLICML-2006-HertzBW #kernel #learning
Learning a kernel function for classification with small training samples (TH, ABH, DW), pp. 401–408.
ICMLICML-2006-HoiJZL #image #learning
Batch mode active learning and its application to medical image classification (SCHH, RJ, JZ, MRL), pp. 417–424.
ICMLICML-2006-KimMSBL #linear
Pareto optimal linear classification (SJK, AM, SS, SPB, JL), pp. 473–480.
ICMLICML-2006-LeeGW #using
Using query-specific variance estimates to combine Bayesian classifiers (CHL, RG, SW), pp. 529–536.
ICMLICML-2006-ReyzinS #complexity #how
How boosting the margin can also boost classifier complexity (LR, RES), pp. 753–760.
ICMLICML-2006-SinghiL #bias #learning #set
Feature subset selection bias for classification learning (SKS, HL), pp. 849–856.
ICMLICML-2006-SuZ #network
Full Bayesian network classifiers (JS, HZ), pp. 897–904.
ICMLICML-2006-XiKSWR #performance #reduction #using
Fast time series classification using numerosity reduction (XX, EJK, CRS, LW, CAR), pp. 1033–1040.
ICPRICPR-v1-2006-ArandjelovicC #set #using
Face Set Classification using Maximally Probable Mutual Modes (OA, RC), pp. 511–514.
ICPRICPR-v1-2006-ArzhaevaGT #detection #distance #image
Image Classification from Generalized Image Distance Features: Application to Detection of Interstitial Disease in Chest Radiographs (YA, BvG, DMJT), pp. 367–370.
ICPRICPR-v1-2006-BoschMOM #approach #question #what
Object and Scene Classification: what does a Supervised Approach Provide us? (AB, XM, AO, RM), pp. 773–777.
ICPRICPR-v1-2006-ConduracheA #2d #image #linear #segmentation #using
Vessel Segmentation in 2D-Projection Images Using a Supervised Linear Hysteresis Classifier (AC, TA), pp. 343–346.
ICPRICPR-v1-2006-FuCLR #feature model #image
Boosted Band Ratio Feature Selection for Hyperspectral Image Classification (ZF, TC, NL, ARK), pp. 1059–1062.
ICPRICPR-v1-2006-KaufholdCHR #recognition #segmentation #using
Recognition and Segmentation of Scene Content using Region-Based Classification (JPK, RC, AH, PR), pp. 755–760.
ICPRICPR-v1-2006-KimK #using
Simultaneous Classification and VisualWord Selection using Entropy-based Minimum Description Length (SK, ISK), pp. 650–653.
ICPRICPR-v1-2006-MarmoAC #set #using
Microfossils shape classification using a set of width values (RM, SA, VC), pp. 691–694.
ICPRICPR-v1-2006-NegriCMP #algorithm
An Oriented-Contour Point Based Voting Algorithm for Vehicle Type Classification (PN, XC, MM, RP), pp. 574–577.
ICPRICPR-v1-2006-PrehnS #adaptation #algorithm #clustering #incremental #robust #using
An Adaptive Classification Algorithm Using Robust Incremental Clustering (HP, GS), pp. 896–899.
ICPRICPR-v1-2006-SunSM #simulation
The Role of Featural and Configural Information in Face Classification A Simulation of the Expertise Hypothesis (YS, NS, MM), pp. 1166–1170.
ICPRICPR-v1-2006-ThurauHB #behaviour #game studies #video
Classification of Team Behaviors in Sports Video Games (CT, TH, CB), pp. 1188–1191.
ICPRICPR-v1-2006-WongC #gesture #recognition #using
Continuous Gesture Recognition using a Sparse Bayesian Classifier (SFW, RC), pp. 1084–1087.
ICPRICPR-v1-2006-WongLI
Brush Writing Style Classification from Individual Chinese Characters (STSW, HL, HHSI), pp. 884–887.
ICPRICPR-v1-2006-ZhangLSC #corpus #performance
An Efficient SVM Classifier for Lopsided Corpora (XZ, BCL, WS, LC), pp. 1144–1147.
ICPRICPR-v1-2006-ZhuWCW #human-computer #interface #predict
GMM-Based Classification Method for Continuous Prediction in Brain-Computer Interface (XZ, JW, YC, YW), pp. 1171–1174.
ICPRICPR-v2-2006-ArivazhaganGK #statistics #using
Texture classification using Curvelet Statistical and Co-occurrence Features (SA, LG, TGSK), pp. 938–941.
ICPRICPR-v2-2006-BertolamiB #integration #multi #recognition
Early feature stream integration versus decision level combination in a multiple classifier system for text line recognition (RB, HB), pp. 845–848.
ICPRICPR-v2-2006-BhuiyanN #detection #image #using
Anti-personnel Mine Detection and Classification Using GPR Image (AB, BN), pp. 1082–1085.
ICPRICPR-v2-2006-ChenB #invariant #using
Invariant Texture Classification Using Ridgelet Packets (GC, PB), pp. 464–467.
ICPRICPR-v2-2006-ChiangK #using
Classification of Line and Character Pixels on Raster Maps Using Discrete Cosine Transformation Coefficients and Support Vector Machine (YYC, CAK), pp. 1034–1037.
ICPRICPR-v2-2006-ChoiLY #feature model #using
Feature Extraction for Bank Note Classification Using Wavelet Transform (EC, JL, JY), pp. 934–937.
ICPRICPR-v2-2006-DengHG #algorithm
Ada-Boost Algorithm, Classification, Naïve- (WD, JH, JG), pp. 699–702.
ICPRICPR-v2-2006-DonateDR
Classification of Textures Distorted by WaterWaves (AD, GD, ER), pp. 421–424.
ICPRICPR-v2-2006-Ekbal #predict #using
Improvement of Prediction Accuracy Using Discretization and Voting Classifier (AE), pp. 695–698.
ICPRICPR-v2-2006-FangQ
Car/Non-Car Classification in an Informative Sample Subspace (JF, GQ), pp. 962–965.
ICPRICPR-v2-2006-GaoLL #approach #learning #optimisation
An ensemble classifier learning approach to ROC optimization (SG, CHL, JHL), pp. 679–682.
ICPRICPR-v2-2006-GuptaRPH
Classifiers for Motion (MDG, SR, NP, TSH), pp. 593–596.
ICPRICPR-v2-2006-Hotta #adaptation
Adaptive Weighting of Local Classifiers by Particle Filter (KH), pp. 610–613.
ICPRICPR-v2-2006-HuD #multi #theorem
A “No Panacea Theorem” for Multiple Classifier Combination (RH, RID), pp. 1250–1253.
ICPRICPR-v2-2006-IlonenPKK
Gaussian mixture pdf in one-class classification: computing and utilizing confidence values (JI, PP, JKK, HK), pp. 577–580.
ICPRICPR-v2-2006-KelmPM #generative #learning #multi
Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning (BMK, CP, AM), pp. 828–832.
ICPRICPR-v2-2006-KennedyNS
An LVQ-based Automotive Occupant Classification System (KRK, JFN, MS), pp. 662–665.
ICPRICPR-v2-2006-LefebvreLRG #comparison #image #process
Supervised Image Classification by SOM Activity Map Comparison (GL, CL, JR, CG), pp. 728–731.
ICPRICPR-v2-2006-LernerM #image #learning #network
Learning Bayesian Networks for Cytogenetic Image Classification (BL, RM), pp. 772–775.
ICPRICPR-v2-2006-Liu #feature model #polynomial #recognition #using
High Accuracy Handwritten Chinese Character Recognition Using Quadratic Classifiers with Discriminative Feature Extraction (CLL), pp. 942–945.
ICPRICPR-v2-2006-LiuL #image #using
Genus-Zero Shape Classification Using Spherical Normal Image (SL, JL), pp. 126–129.
ICPRICPR-v2-2006-McDanielKP #approach #visual notation
A Bayesian Approach to Visual Size Classification of Everyday Objects (TLM, KK, SP), pp. 255–259.
ICPRICPR-v2-2006-NandedkarB #fuzzy #network
A Reflex Fuzzy Min Max Neural Network for Granular Data Classification (AVN, PKB), pp. 650–653.
ICPRICPR-v2-2006-QinWHG #automation
Unsupervised Texture Classification: Automatically Discover and Classify Texture Patterns (LQ, WW, QH, WG), pp. 433–436.
ICPRICPR-v2-2006-Sarkar #image #visual notation
Image classification: Classifying distributions of visual features (PS), pp. 472–475.
ICPRICPR-v2-2006-ShimshoniRS #image #performance #verification
Efficient Search and Verification for Function Based Classification from Real Range Images (IS, ER, OS), pp. 1118–1121.
ICPRICPR-v2-2006-SuSCG #recognition
Patch-Based Gabor Fisher Classifier for Face Recognition (YS, SS, XC, WG), pp. 528–531.
ICPRICPR-v2-2006-ThakoorJWG
Occlusion Resistant Shape Classifier based onWarped Optimal Path Matching (NT, SJ, QW, JG), pp. 60–63.
ICPRICPR-v2-2006-TsuchiyaF #visual notation
Evaluating Feature Importance for Object Classification in Visual Surveillance (MT, HF), pp. 978–981.
ICPRICPR-v2-2006-UekiHK #2d #analysis #linear
Two-dimensional Heteroscedastic Linear Discriminant Analysis for Age-group Classification (KU, TH, TK), pp. 585–588.
ICPRICPR-v2-2006-WimmerRB #approach
A Person and Context Specific Approach for Skin Color Classification (MW, BR, MB), pp. 39–42.
ICPRICPR-v2-2006-YaslanC #feature model #music #using
Audio Music Genre Classification Using Different Classifiers and Feature Selection Methods (YY, ), pp. 573–576.
ICPRICPR-v2-2006-YuanQYZ #approach #kernel
An Approach for Constructing Sparse Kernel Classifier (ZY, YQ, YY, NZ), pp. 560–563.
ICPRICPR-v2-2006-ZhangC #locality
Comparing Different Localization Approaches of the Radon Transform for Road Centerline Extraction from Classified Satellite Imagery (QZ, IC), pp. 138–141.
ICPRICPR-v2-2006-ZhangPB #learning #representation
Learning Optimal Filter Representation for Texture Classification (PZ, JP, BPB), pp. 1138–1141.
ICPRICPR-v2-2006-ZhengYYW #effectiveness #image #problem
Effective classification image space which can solve small sample size problem (YJZ, JYY, JY, XW), pp. 861–864.
ICPRICPR-v3-2006-AbdulkaderDZ #comparative
Comparative Classifier Aggregation (AA, JAD, QZ), pp. 156–159.
ICPRICPR-v3-2006-AnLV #performance
Efficient Cross-validation of the Complete Two Stages in KFD Classifier Formulation (SA, WL, SV), pp. 240–244.
ICPRICPR-v3-2006-ArreolaFB #linear #performance #using
Fast Support Vector Machine Classification using linear SVMs (KZA, JF, HB), pp. 366–369.
ICPRICPR-v3-2006-BarbuRLAHT #algorithm #graph #recognition #search-based #using
Graph Classification Using Genetic Algorithm and Graph Probing Application to Symbol Recognition (EB, RR, HL, SA, PH, ÉT), pp. 296–299.
ICPRICPR-v3-2006-BauckhageK06a #multi
Benefits of Separable, Multilinear Discriminant Classification (CB, TK), pp. 1240–1243.
ICPRICPR-v3-2006-BeveridgeSR #comparison #detection #naive bayes #using
A Comparison of Pixel, Edge andWavelet Features for Face Detection using a Semi-Naive Bayesian Classifier (JRB, JS, BR), pp. 1175–1178.
ICPRICPR-v3-2006-HarmoucheCAFA #modelling
Bayesian MS Lesion Classification Modeling Regional and Local Spatial Information (RH, DLC, DLA, SJF, TA), pp. 984–987.
ICPRICPR-v3-2006-HuS06a #clustering #functional #image #normalisation
Normalization of Functional Magnetic Resonance Images by Classified Cerebrospinal Fluid Cluster (ZH, PS), pp. 938–941.
ICPRICPR-v3-2006-JiaZHW
Gaussian Weighted Histogram Intersection for License Plate Classification (WJ, HZ, XH, QW), pp. 574–577.
ICPRICPR-v3-2006-KierA #multi #predict
Predicting the benefit of sample size extension in multiclass k-NN classification (CK, TA), pp. 332–335.
ICPRICPR-v3-2006-KovalevP
The Classification Gradient (VAK, MP), pp. 830–833.
ICPRICPR-v3-2006-LeeP #detection #robust
Robust vehicle detection based on shadow classification (DL, YP), pp. 1167–1170.
ICPRICPR-v3-2006-LernerV #fuzzy #image #search-based #using
Image Classification for Genetic Diagnosis using Fuzzy ARTMAP (BL, BV), pp. 362–365.
ICPRICPR-v3-2006-LiC #nearest neighbour #probability #using
Classification Using the Local Probabilistic Centers of k-Nearest Neighbors (BYL, YWC), pp. 1220–1223.
ICPRICPR-v3-2006-LouJ #adaptation #nearest neighbour #novel
Novel Adaptive Nearest Neighbor Classifiers Based On Hit-Distance (ZL, ZJ), pp. 87–90.
ICPRICPR-v3-2006-Martinez-ArroyoS #learning #naive bayes
Learning an Optimal Naive Bayes Classifier (MMA, LES), pp. 1236–1239.
ICPRICPR-v3-2006-MatosC #network
Combining global and local classifiers with Bayesian network (LNM, JMdC), pp. 1212–1215.
ICPRICPR-v3-2006-NagasakiMKS #adaptation #image
A Coupon Classification Method Based on Adaptive Image Vector Matching (TN, KM, TK, HS), pp. 280–283.
ICPRICPR-v3-2006-PaclikND #image #similarity
A Trainable Similarity Measure for Image Classification (PP, JN, RPWD), pp. 391–394.
ICPRICPR-v3-2006-PekalskaD
Dissimilarity-based classification for vectorial representations (EP, RPWD), pp. 137–140.
ICPRICPR-v3-2006-TscherepanowZK #image
Classification of Segmented Regions in Brightfield Microscope Images (MT, FZ, FK), pp. 972–975.
ICPRICPR-v3-2006-Wang06b #image
Colony Delineation on Image Classification (WW), pp. 705–708.
ICPRICPR-v3-2006-WangNC #approach
A Minimum Sphere Covering Approach to Pattern Classification (JW, PN, LNC), pp. 433–436.
ICPRICPR-v3-2006-WongLY #performance
Improving Text Classifier Performance based on AUC (AKSW, JWTL, DSY), pp. 268–271.
ICPRICPR-v3-2006-WongWC #robust #using
Robust Appearance-based Tracking using a sparse Bayesian classifier (SFW, KYKW, RC), pp. 47–50.
ICPRICPR-v3-2006-XuanCZYHSF #analysis #component #novel
A Novel Pattern Classification Scheme: Classwise Non-Principal Component Analysis (CNPCA) (GX, PC, XZ, QY, CH, YQS, DF), pp. 320–323.
ICPRICPR-v3-2006-YangLA #automation #case study #gender
An Experimental Study on Automatic Face Gender Classification (ZY, ML, HA), pp. 1099–1102.
ICPRICPR-v3-2006-YinNFMA #statistics
Statistical Model for the Classification of the Wavelet Transforms of T-ray Pulses (XXY, BWHN, BF, SPM, DA), pp. 236–239.
ICPRICPR-v3-2006-YuHSLPGF
Shape-based Discrimination and Classification of Cortical Surfaces (PY, XH, FS, AKL, RAP, PG, BF), pp. 445–448.
ICPRICPR-v3-2006-ZhangR06a #integration #robust #visual notation
Robust Visual Tracking via Pixel Classification and Integration (CZ, YR), pp. 37–42.
ICPRICPR-v3-2006-ZouB #energy #image #process #programming #search-based
Human Activity Classification Based on Gait Energy Image and Coevolutionary Genetic Programming (XZ, BB), pp. 556–559.
ICPRICPR-v4-2006-AndraN
Combining Dichotomizers for MAP Field Classification (SA, GN), pp. 210–214.
ICPRICPR-v4-2006-BauckhageK06b #multi
Benefits of Separable, Multilinear Discriminant Classification (CB, TK), p. 959.
ICPRICPR-v4-2006-Fisher06a #capacity #empirical
An Empirical Model for Saturation and Capacity in Classifier Spaces (RBF), pp. 189–193.
ICPRICPR-v4-2006-JinYSLX #detection #hybrid #precise #robust
A hybrid classifier for precise and robust eye detection (LJ, XHY, SS, JL, LX), pp. 731–735.
ICPRICPR-v4-2006-LefaucheurN #multi #robust #symmetry
Robust Multiclass Ensemble Classifiers via Symmetric Functions (PL, RN), pp. 136–139.
ICPRICPR-v4-2006-LiaoS
Classification of Audio Signals in All-Night Sleep Studies (WHL, YSS), pp. 302–305.
ICPRICPR-v4-2006-LiC06a #nearest neighbour #probability #using
Classification Using the Local Probabilistic Centers of k-Nearest Neighbors (BYL, YWC), p. 954.
ICPRICPR-v4-2006-Martinez-ArroyoS06a #learning #naive bayes
Learning an Optimal Naive Bayes Classifier (MMA, LES), p. 958.
ICPRICPR-v4-2006-MatosC06a #network
Combining global and local classifiers with Bayesian network (LNM, JMdC), p. 952.
ICPRICPR-v4-2006-OliverMMBF #approach
A new approach to the classification of mammographic masses and normal breast tissue (AO, JM, RM, AB, JF), pp. 707–710.
ICPRICPR-v4-2006-PhamS #approximate #clustering #metric #performance
Metric tree partitioning and Taylor approximation for fast support vector classification (TVP, AWMS), pp. 132–135.
ICPRICPR-v4-2006-TiviveB #gender #network
A Shunting Inhibitory Convolutional Neural Network for Gender Classification (FHCT, AB), pp. 421–424.
ICPRICPR-v4-2006-TodorovicA #3d #segmentation #using
3D Texture Classification Using the Belief Net of a Segmentation Tree (ST, NA), pp. 33–36.
ICPRICPR-v4-2006-Wang06d #metric #process #profiling
From Blob Metrics to Posture Classification to Activity Profiling (LW0), pp. 736–739.
ICPRICPR-v4-2006-WangWLJK #analysis #component #independence #using
Content-Based Audio Classification Using Support Vector Machines and Independent Component Analysis (JCW, JFW, CBL, KTJ, WHK), pp. 157–160.
ICPRICPR-v4-2006-WangXC #2d #automation #pseudo #using #video
Automatic Sports Video Genre Classification using Pseudo-2D-HMM (JW, CX, EC), pp. 778–781.
ICPRICPR-v4-2006-WongN
Blind Phase-Amplitude Modulation Classification with Unknown Phase Offset (MLDW, AKN), pp. 177–180.
ICPRICPR-v4-2006-XuC #invariant #multi
Multiscale Blob Features for Gray Scale, Rotation and Spatial Scale Invariant Texture Classification (QX, YQC), pp. 29–32.
KDDKDD-2006-ArunasalamC #named #top-down
CCCS: a top-down associative classifier for imbalanced class distribution (BA, SC), pp. 517–522.
KDDKDD-2006-BiPOKFSR #detection #symmetry
Computer aided detection via asymmetric cascade of sparse hyperplane classifiers (JB, SP, KO, TK, GF, MS, RBR), pp. 837–844.
KDDKDD-2006-BurkeMWB #collaboration #detection #recommendation
Classification features for attack detection in collaborative recommender systems (RDB, BM, CW, RB), pp. 542–547.
KDDKDD-2006-CastanoMTGDCCD #detection
Onboard classifiers for science event detection on a remote sensing spacecraft (RC, DM, NT, RG, TD, BC, SAC, AD), pp. 845–851.
KDDKDD-2006-FanD #bias #framework #performance #testing
Reverse testing: an efficient framework to select amongst classifiers under sample selection bias (WF, ID), pp. 147–156.
KDDKDD-2006-Forman #fault #roadmap
Quantifying trends accurately despite classifier error and class imbalance (GF), pp. 157–166.
KDDKDD-2006-HoiLC #kernel #learning
Learning the unified kernel machines for classification (SCHH, MRL, EYC), pp. 187–196.
KDDKDD-2006-NathBM #approach #clustering #scalability #using
Clustering based large margin classification: a scalable approach using SOCP formulation (JSN, CB, MNM), pp. 674–679.
KDDKDD-2006-TangZL #data-driven #semantics #taxonomy
Acclimatizing taxonomic semantics for hierarchical content classification from semantics to data-driven taxonomy (LT, JZ, HL), pp. 384–393.
KDDKDD-2006-WeiK
Semi-supervised time series classification (LW, EJK), pp. 748–753.
KDDKDD-2006-YanB #optimisation #ranking
Beyond classification and ranking: constrained optimization of the ROI (LY, PB), pp. 948–953.
KDDKDD-2006-ZhangL #string
Extracting key-substring-group features for text classification (DZ, WSL), pp. 474–483.
SEKESEKE-2006-ZengA #multi #representation
Classification by Multi-Perspective Representation Method (JZ, RA), pp. 85–90.
SIGIRSIGIR-2006-AngelovaW #graph
Graph-based text classification: learn from your neighbors (RA, GW), pp. 485–492.
SIGIRSIGIR-2006-BlunsomKC #modelling
Question classification with log-linear models (PB, KK, JRC), pp. 615–616.
SIGIRSIGIR-2006-DayanikLMMG
Constructing informative prior distributions from domain knowledge in text classification (AAD, DDL, DM, VM, AG), pp. 493–500.
SIGIRSIGIR-2006-Olsson #analysis #set
An analysis of the coupling between training set and neighborhood sizes for the kNN classifier (JSO), pp. 685–686.
SIGIRSIGIR-2006-ShenSYC #query #web
Building bridges for web query classification (DS, JTS, QY, ZC), pp. 131–138.
SIGIRSIGIR-2006-SteinAF #fault
The effect of OCR errors on stylistic text classification (SSS, SA, OF), pp. 701–702.
QAPLQAPL-2005-LanotteMT06 #probability #security
A Classification of Time and/or Probability Dependent Security Properties (RL, AMS, AT), pp. 177–193.
RERE-2006-Cleland-HuangSZS #aspect-oriented #detection #non-functional #requirements
The Detection and Classification of Non-Functional Requirements with Application to Early Aspects (JCH, RS, XZ, PS), pp. 36–45.
ASEASE-2006-dAmorimPXME #automation #comparison #empirical #generative #object-oriented #testing
An Empirical Comparison of Automated Generation and Classification Techniques for Object-Oriented Unit Testing (Md, CP, TX, DM, MDE), pp. 59–68.
FSEFSE-2006-StorzerRRT #java #source code #using
Finding failure-inducing changes in java programs using change classification (MS, BGR, XR, FT), pp. 57–68.
ICSEICSE-2006-AbeMKKH #estimation #using
Estimation of project success using Bayesian classifier (SA, OM, TK, NK, MH), pp. 600–603.
SACSAC-2006-AbidinP #data mining #mining #named #nearest neighbour #performance #scalability
SMART-TV: a fast and scalable nearest neighbor based classifier for data mining (TA, WP), pp. 536–540.
SACSAC-2006-BelsisFGS
SF-HME system: a hierarchical mixtures-of-experts classification system for spam filtering (PB, KF, SG, CS), pp. 354–360.
SACSAC-2006-CraigL #learning #using
Protein classification using transductive learning on phylogenetic profiles (RAC, LL), pp. 161–166.
SACSAC-2006-FelipeRSTT #effectiveness #retrieval
Effective shape-based retrieval and classification of mammograms (JCF, MXR, EPMdS, AJMT, CTJ), pp. 250–255.
SACSAC-2006-Ferrer-TroyanoAS #data type #incremental #learning
Data streams classification by incremental rule learning with parameterized generalization (FJFT, JSAR, JCRS), pp. 657–661.
SACSAC-2006-ForteSP #internet
A content classification and filtering server for the internet (MF, WLdS, AFdP), pp. 1166–1171.
SACSAC-2006-MerschmannP #approach
A Bayesian approach for protein classification (LHdCM, AP), pp. 200–201.
SACSAC-2006-TailbyDMS #automation #email
Email classification for automated service handling (RT, RD, BM, DS), pp. 1073–1077.
SACSAC-2006-XingMXV #documentation #edit distance #xml
Computing edit distances between an XML document and a schema and its application in document classification (GX, CRM, ZX, SDV), pp. 831–835.
SACSAC-2006-ZamolotskikhDC #bias
A methodology for comparing classifiers that allow the control of bias (AZ, SJD, PC), pp. 582–587.
DATEDATE-2006-IgnatNSN #impact analysis #operating system #realtime
Soft-error classification and impact analysis on real-time operating systems (NI, BN, YS, GN), pp. 182–187.
DATEDATE-2006-KruppM #functional #random testing #testing
Classification trees for random tests and functional coverage (AK, WM), pp. 1031–1032.
DATEDATE-DF-2006-PapaefstathiouP
A hardware-engine for layer-2 classification in low-storage, ultra-high bandwidth environments (VP, IP), pp. 112–117.
MBTMBT-2006-ConradK #embedded
An Extension of the Classification-Tree Method for Embedded Systems for the Description of Events (MC, AK), pp. 3–11.
DocEngDocEng-2005-SimskeLA #image #statistics
A statistical method for binary classification of images (SJS, DL, JSA), pp. 127–129.
TPDLECDL-2005-BalkeNST #distributed #documentation #retrieval
DL Meets P2P — Distributed Document Retrieval Based on Classification and Content (WTB, WN, WS, UT), pp. 379–390.
TPDLECDL-2005-GolubA #automation #html #metadata
Importance of HTML Structural Elements and Metadata in Automated Subject Classification (KG, AA), pp. 368–378.
TPDLECDL-2005-KimJC #automation #library #naive bayes #ontology #semantics
Building Semantic Digital Libraries: Automated Ontology Linking by Associative Naïve Bayes Classifier (HK, MGJ, SSC), pp. 500–501.
ICDARICDAR-2005-BhagvatiD #using
Classification of Liquid and Viscous Inks using HSV Colour Space (CB, HD), pp. 660–664.
ICDARICDAR-2005-BhattacharyaC #recognition
Fusion of Combination Rules of an Ensemble of MLP Classifiers for Improved Recognition Accuracy of Handprinted Bangla Numerals (UB, BBC), pp. 322–326.
ICDARICDAR-2005-DuongE #design #recognition
Cascade Classifier : Design and Application to Digit Recognition (JD, HE), pp. 1065–1069.
ICDARICDAR-2005-FarahEKS #multi #recognition #word
Benefit of multiclassifier systems for Arabic handwritten words recognition (NF, AE, TK, MS), pp. 222–226.
ICDARICDAR-2005-FengM #modelling #recognition
Classification Models for Historical Manuscript Recognition (SF, RM), pp. 528–532.
ICDARICDAR-2005-IshitaniFS #analysis #documentation #xml
Table Structure Analysis Based on Cell Classification and Cell Modification for XML Document Transformation (YI, KF, KS), pp. 1247–1252.
ICDARICDAR-2005-KangD #multi
Selection of Classifiers for the Construction of Multiple Classifier Systems (HJK, DSD), pp. 1194–1198.
ICDARICDAR-2005-LeiG #sequence
Similarity-driven Sequence Classification Based on Support Vector Machines (HL, VG), pp. 252–261.
ICDARICDAR-2005-LiuD #multi #polynomial #recognition #using
Handwritten Character Recognition Using Gradient Feature and Quadratic Classifier with Multiple Discrimination Schemes (HL, XD), pp. 19–25.
ICDARICDAR-2005-LiuMK #feature model #recognition #scalability #set #using
Building Compact Classifier for Large Character Set Recognition Using Discriminative Feature Extraction (CLL, RM, MK), pp. 846–850.
ICDARICDAR-2005-LiuWD #detection #image
Text Detection in Images Based on Unsupervised Classification of Edge-based Features (CL, CW, RD), pp. 610–614.
ICDARICDAR-2005-MoussaZAB
Can Fractal Dimension Be Used In Font Classification (SBM, AZ, AMA, AB), pp. 146–150.
ICDARICDAR-2005-OliveiraBS05a #optimisation
Improving Cascading Classifiers with Particle Swarm Optimization (LSO, AdSBJ, RS), pp. 570–574.
ICDARICDAR-2005-PrudentE #multi
A Toplogy Based Multi-Classifier System (YP, AE), pp. 670–674.
ICDARICDAR-2005-RadtkeSW #feature model
Intelligent Feature Extraction for Ensemble of Classifiers (PVWR, RS, TW), pp. 866–870.
ICDARICDAR-2005-WangC #using
A Hierarchical Classifier Using New Support Vector Machine (YCFW, DC), pp. 851–855.
JCDLJCDL-2005-FuKM #automation #framework #multi #using
Automated text classification using a multi-agent framework (YF, WK, JM), pp. 157–158.
VLDBVLDB-2005-LimWV #estimation #online #string #xml
CXHist : An On-line Classification-Based Histogram for XML String Selectivity Estimation (LL, MW, JSV), pp. 1187–1198.
VLDBVLDB-2005-MeierWAS #fuzzy #query #using
Using a Fuzzy Classification Query Language for Customer Relationship Management (AM, NW, MA, MS), pp. 1089–1096.
ICSMEICSM-2005-MarinMD
A Classification of Crosscutting Concerns (MM, LM, AvD), pp. 673–676.
SCAMSCAM-2005-PowerH #java #named #source code
Declassification: Transforming Java Programs to Remove Intermediate Classes (BP, GWH), pp. 183–192.
ICALPICALP-2005-BraekenBNP #encryption
Classification of Boolean Functions of 6 Variables or Less with Respect to Some Cryptographic Properties (AB, YLB, SN, BP), pp. 324–334.
DiGRADiGRA-2005-ElverdamA #analysis #design #game studies
Game Classification as Game Design: Construction Through Critical Analysis (CE, EA).
ICEISICEIS-v2-2005-NilssonFX #using
Clinical Decision Support by Time Series Classification Using Wavelets (MN, PF, NX), pp. 169–175.
ICEISICEIS-v2-2005-Ruta #multi
Multidimensional Selection Model for Classification (DR), pp. 226–232.
ICEISICEIS-v5-2005-DixitM #documentation #using
Electronic Document Classification Using Support Vector Machine — An Application for E-Learning (SD, LKM), pp. 191–198.
CIKMCIKM-2005-BoeseH #documentation #evolution #web
Effects of web document evolution on genre classification (ESB, AEH), pp. 632–639.
CIKMCIKM-2005-BotWCL #automation #concept #documentation #generative #using
Generating better concept hierarchies using automatic document classification (RSB, YfBW, XC, QL), pp. 281–282.
CIKMCIKM-2005-EsuliS #semantics
Determining the semantic orientation of terms through gloss classification (AE, FS), pp. 617–624.
CIKMCIKM-2005-GhamrawiM #multi
Collective multi-label classification (NG, AM), pp. 195–200.
CIKMCIKM-2005-KanT #performance #using
Fast webpage classification using URL features (MYK, HONT), pp. 325–326.
CIKMCIKM-2005-WangNZ #semantics
A latent semantic classification model (MWW, JYN, XQZ), pp. 261–262.
CIKMCIKM-2005-ZhangCFFGCC #multi
Intelligent GP fusion from multiple sources for text classification (BZ, YC, WF, EAF, MAG, MC, PC), pp. 477–484.
ECIRECIR-2005-AyacheQC #using #video
Video Shot Classification Using Lexical Context (SA, GQ, MC), pp. 549–551.
ECIRECIR-2005-MartonWH #on the
On Compression-Based Text Classification (YM, NW, LH), pp. 300–314.
ECIRECIR-2005-SiersdorferW #strict #using
Using Restrictive Classification and Meta Classification for Junk Elimination (SS, GW), pp. 287–299.
ICMLICML-2005-BeygelzimerDHLZ #fault #reduction
Error limiting reductions between classification tasks (AB, VD, TPH, JL, BZ), pp. 49–56.
ICMLICML-2005-EspositoS #comparison #monte carlo
Experimental comparison between bagging and Monte Carlo ensemble classification (RE, LS), pp. 209–216.
ICMLICML-2005-GlocerET #feature model #online
Online feature selection for pixel classification (KAG, DE, JT), pp. 249–256.
ICMLICML-2005-HillD #adaptation #problem
Adapting two-class support vector classification methods to many class problems (SIH, AD), pp. 313–320.
ICMLICML-2005-JingPR #learning #naive bayes #network #performance
Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes (YJ, VP, JMR), pp. 369–376.
ICMLICML-2005-Keerthi #effectiveness #feature model
Generalized LARS as an effective feature selection tool for text classification with SVMs (SSK), pp. 417–424.
ICMLICML-2005-KhoussainovHK
Ensembles of biased classifiers (RK, AH, NK), pp. 425–432.
ICMLICML-2005-LangfordZ #learning #performance
Relating reinforcement learning performance to classification performance (JL, BZ), pp. 473–480.
ICMLICML-2005-LavioletteM #bound
PAC-Bayes risk bounds for sample-compressed Gibbs classifiers (FL, MM), pp. 481–488.
ICMLICML-2005-LeiteB #performance #predict
Predicting relative performance of classifiers from samples (RL, PB), pp. 497–503.
ICMLICML-2005-MannorPR
The cross entropy method for classification (SM, DP, RYR), pp. 561–568.
ICMLICML-2005-PernkopfB #generative #learning #network #parametricity
Discriminative versus generative parameter and structure learning of Bayesian network classifiers (FP, JAB), pp. 657–664.
ICMLICML-2005-Pietraszek #analysis #optimisation #using
Optimizing abstaining classifiers using ROC analysis (TP), pp. 665–672.
ICMLICML-2005-RamakrishnanCKB #approximate
A model for handling approximate, noisy or incomplete labeling in text classification (GR, KPC, RK, PB), pp. 681–688.
ICMLICML-2005-RousuSSS #learning #modelling #multi
Learning hierarchical multi-category text classification models (JR, CS, SS, JST), pp. 744–751.
ICMLICML-2005-SonnenburgRS #scalability #sequence
Large scale genomic sequence SVM classifiers (SS, GR, BS), pp. 848–855.
ICMLICML-2005-VeeramachaneniSA #documentation
Hierarchical Dirichlet model for document classification (SV, DS, PA), pp. 928–935.
ICMLICML-2005-WangS #kernel
New kernels for protein structural motif discovery and function classification (CW, SDS), pp. 940–947.
ICMLICML-2005-WilliamsLXC #using
Incomplete-data classification using logistic regression (DW, XL, YX, LC), pp. 972–979.
ICMLICML-2005-WuMR #detection #linear #symmetry
Linear Asymmetric Classifier for cascade detectors (JW, MDM, JMR), pp. 988–995.
ICMLICML-2005-WuSB #scalability
Building Sparse Large Margin Classifiers (MW, BS, GHB), pp. 996–1003.
KDDKDD-2005-Aggarwal #algorithm #towards
Towards exploratory test instance specific algorithms for high dimensional classification (CCA), pp. 526–531.
KDDKDD-2005-ChenH #analysis #image #network
A Bayesian network classifier with inverse tree structure for voxelwise magnetic resonance image analysis (RC, EH), pp. 4–12.
KDDKDD-2005-Kolcz #naive bayes
Local sparsity control for naive Bayes with extreme misclassification costs (AK), pp. 128–137.
KDDKDD-2005-ManeSH #independence #using
Estimating missed actual positives using independent classifiers (SM, JS, SYH), pp. 648–653.
KDDKDD-2005-Sandler #linear #on the #programming #using
On the use of linear programming for unsupervised text classification (MS), pp. 256–264.
KDDKDD-2005-ZhangWZ #privacy
A new scheme on privacy-preserving data classification (NZ, SW, WZ), pp. 374–383.
MLDMMLDM-2005-Bak #linear #multi
A New Multidimensional Feature Transformation for Linear Classifiers and Its Applications (EB), pp. 275–284.
MLDMMLDM-2005-GuptaKB #concept analysis #incremental #using
Incremental Classification Rules Based on Association Rules Using Formal Concept Analysis (AG, NK, VB), pp. 11–20.
MLDMMLDM-2005-HayashiMS
Embedding Time Series Data for Classification (AH, YM, NS), pp. 356–365.
MLDMMLDM-2005-KoK #on the
On ECOC as Binary Ensemble Classifiers (JK, EK), pp. 1–10.
MLDMMLDM-2005-LeHS #ambiguity #approach #reasoning #word
An Evidential Reasoning Approach to Weighted Combination of Classifiers for Word Sense Disambiguation (CAL, VNH, AS), pp. 516–525.
MLDMMLDM-2005-MakrehchiK #using
Text Classification Using Small Number of Features (MM, MSK), pp. 580–589.
MLDMMLDM-2005-SzepannekLW #comprehension
Understanding Patterns with Different Subspace Classification (GS, KL, CW), pp. 110–119.
MLDMMLDM-2005-TakigawaKN #combinator #product line #set #subclass
The Convex Subclass Method: Combinatorial Classifier Based on a Family of Convex Sets (IT, MK, AN), pp. 90–99.
SEKESEKE-2005-ChiangTK #multi #performance #using
Fast Class Rendering Using Multiresolution Classification in Discrete Cosine Transform Domain (TWC, TT, LJK), pp. 689–694.
SIGIRSIGIR-2005-BeitzelJFGLCK #automation #query #using #web
Automatic web query classification using labeled and unlabeled training data (SMB, ECJ, OF, DAG, DDL, AC, AK), pp. 581–582.
SIGIRSIGIR-2005-CarvalhoC #email #on the #speech
On the collective classification of email “speech acts” (VRdC, WWC), pp. 345–352.
SIGIRSIGIR-2005-MaL #automation #documentation #paradigm #semantics
A phonotactic-semantic paradigm for automatic spoken document classification (BM, HL), pp. 369–376.
SIGIRSIGIR-2005-OlssonOH
Cross-language text classification (JSO, DWO, JH), pp. 645–646.
SIGIRSIGIR-2005-TanCWXGG #using
Using dragpushing to refine centroid text classifiers (ST, XC, BW, HX, MG, YG), pp. 653–654.
SIGIRSIGIR-2005-ZhangCFFGCC
Intelligent fusion of structural and citation-based evidence for text classification (BZ, YC, WF, EAF, MAG, MC, PC), pp. 667–668.
SIGIRSIGIR-2005-ZhangCL #kernel #multi
Text classification with kernels on the multinomial manifold (DZ, XC, WSL), pp. 266–273.
SIGIRSIGIR-2005-ZhuJXG #multi #using
Multi-labelled classification using maximum entropy method (SZ, XJ, WX, YG), pp. 274–281.
ECOOPECOOP-2005-PachecoE #automation #generative #named #testing
Eclat: Automatic Generation and Classification of Test Inputs (CP, MDE), pp. 504–527.
ESEC-FSEESEC-FSE-2005-HaranKOPS #execution
Applying classification techniques to remotely-collected program execution data (MH, AFK, AO, AAP, APS), pp. 146–155.
ICSEICSE-2005-HostWT #experience
Experimental context classification: incentives and experience of subjects (MH, CW, TT), pp. 470–478.
SACSAC-2005-DalkilicS05a #design #implementation #named
Circle: design and implementation of a classifier based on circuit minimization (MMD, AS), pp. 547–548.
SACSAC-2005-DongH #clustering #parametricity
Text classification based on data partitioning and parameter varying ensembles (YSD, KSH), pp. 1044–1048.
SACSAC-2005-FradkinK #learning
Methods for learning classifier combinations: no clear winner (DF, PBK), pp. 1038–1043.
SACSAC-2005-HacheyG #modelling #sequence #summary
Sequence modelling for sentence classification in a legal summarisation system (BH, CG), pp. 292–296.
SACSAC-2005-LiY #predict #recursion #using
Using recursive classification to discover predictive features (FL, YY), pp. 1054–1058.
SACSAC-2005-OcaGA #algorithm #clustering #network
An hybridization of an ant-based clustering algorithm with growing neural gas networks for classification tasks (MAMdO, LG, JLA), pp. 9–13.
SACSAC-2005-QianZQ #image
Spatial contextual noise removal for post classification smoothing of remotely sensed images (YQ, KZ, FQ), pp. 524–528.
CGOCGO-2005-StephensonA #predict #using
Predicting Unroll Factors Using Supervised Classification (MS, SPA), pp. 123–134.
DACDAC-2005-McGeeN #design #framework #pipes and filters
A lattice-based framework for the classification and design of asynchronous pipelines (PBM, SMN), pp. 491–496.
HPCAHPCA-2005-LauSC #predict
Transition Phase Classification and Prediction (JL, SS, BC), pp. 278–289.
ESOPESOP-2005-GiacobazziM #abstract interpretation #modelling
Adjoining Declassification and Attack Models by Abstract Interpretation (RG, IM), pp. 295–310.
ESOPESOP-2005-TseZ #design
A Design for a Security-Typed Language with Certificate-Based Declassification (ST, SZ), pp. 279–294.
DRRDRR-2004-NagyJKLLMS #parametricity
A nonparametric classifier for unsegmented text (GN, AJ, MSK, YL, DPL, SKM, SCS), pp. 102–108.
HTHT-2004-StottsF #hypermedia
Language-theoretic classification of hypermedia paths (PDS, RF), pp. 40–41.
JCDLJCDL-2004-ChenH #library #multi
Multi-modal classification in digital news libraries (MyC, AGH), pp. 212–213.
JCDLJCDL-2004-FanLXW #concept #nondeterminism #semantics #set #video
Semantic video classification and feature subset selection under context and concept uncertainty (JF, HL, JX, LW), pp. 192–201.
VLDBVLDB-2004-Fan #concept #data type #named
StreamMiner: A Classifier Ensemble-based Engine to Mine Concept-drifting Data Streams (WF), pp. 1257–1260.
ICEISICEIS-v2-2004-KotsiantisP #hybrid #using
A Hybrid Decision Support Tool — Using Ensemble of Classifiers (SBK, PEP), pp. 448–456.
ICEISICEIS-v2-2004-YounesTAR #image
Image Classification According to the Dominant Colour (AAY, IT, HA, YR), pp. 505–510.
ICEISICEIS-v4-2004-MazhelisP #detection
Combining One-Class Classifiers for Mobile-User Substitution Detection (OM, SP), pp. 130–137.
CIKMCIKM-2004-SiersdorferSW #documentation #parametricity
Goal-oriented methods and meta methods for document classification and their parameter tuning (SS, SS, GW), pp. 59–68.
CIKMCIKM-2004-Zhang #information management
Weakly-supervised relation classification for information extraction (ZZ), pp. 581–588.
CIKMCIKM-2004-ZhangGFCFCC
Combining structural and citation-based evidence for text classification (BZ, MAG, WF, YC, EAF, PC, MC), pp. 162–163.
ECIRECIR-2004-MoschittiB
Complex Linguistic Features for Text Classification: A Comprehensive Study (AM, RB), pp. 181–196.
ICMLICML-2004-AltunHS #process #sequence
Gaussian process classification for segmenting and annotating sequences (YA, TH, AJS).
ICMLICML-2004-BohteBG #parametricity #polynomial
Nonparametric classification with polynomial MPMC cascades (SMB, MB, GZG).
ICMLICML-2004-Bouckaert #learning
Estimating replicability of classifier learning experiments (RRB).
ICMLICML-2004-DekelKS #scalability
Large margin hierarchical classification (OD, JK, YS).
ICMLICML-2004-EspositoS #analysis #monte carlo
A Monte Carlo analysis of ensemble classification (RE, LS).
ICMLICML-2004-FerriFH
Delegating classifiers (CF, PAF, JHO).
ICMLICML-2004-Forman #feature model #multi
A pitfall and solution in multi-class feature selection for text classification (GF).
ICMLICML-2004-GrossmanD #learning #network
Learning Bayesian network classifiers by maximizing conditional likelihood (DG, PMD).
ICMLICML-2004-HuangYKL #learning #scalability
Learning large margin classifiers locally and globally (KH, HY, IK, MRL).
ICMLICML-2004-KoppelS #problem #verification
Authorship verification as a one-class classification problem (MK, JS).
ICMLICML-2004-LebanonL #multi
Hyperplane margin classifiers on the multinomial manifold (GL, JDL).
ICMLICML-2004-NguyenWJ #detection #distributed #kernel #using
Decentralized detection and classification using kernel methods (XN, MJW, MIJ).
ICMLICML-2004-Zadrozny #bias #learning
Learning and evaluating classifiers under sample selection bias (BZ).
ICPRICPR-v1-2004-ChengLLC #component #independence #kernel #using
Texture Classification Using Kernel Independent Component Analysi (JC, QL, HL, YWC), pp. 620–623.
ICPRICPR-v1-2004-DmitryD #algorithm #effectiveness
Data Dependent Classifier Fusion for Construction of Stable Effective Algorithms (DV, DK), pp. 144–147.
ICPRICPR-v1-2004-DuinPT #problem
The Characterization of Classification Problems by Classifier Disagreements (RPWD, EP, DMJT), pp. 140–143.
ICPRICPR-v1-2004-GarainCG #multi #recognition
A Multiple-Classifier System for Recognition of Printed Mathematical Symbols (UG, BBC, RPG), pp. 380–383.
ICPRICPR-v1-2004-GllavataEF #detection #image
Text Detection in Images Based on Unsupervised Classification of High-Frequency Wavelet Coefficients (JG, RE, BF), pp. 425–428.
ICPRICPR-v1-2004-GocciaSD #fuzzy #learning #recognition
Learning Optimal Classifier Through Fuzzy Recognition Rate Maximization (MG, CS, SGD), pp. 204–207.
ICPRICPR-v1-2004-HeLZZ #image #web
W-Boost and Its Application to Web Image Classification (JH, ML, HZ, CZ), pp. 148–151.
ICPRICPR-v1-2004-Horikawa #comparison #invariant #kernel
Comparison of Support Vector Machines with Autocorrelation Kernels for Invariant Texture Classification (YH), pp. 660–663.
ICPRICPR-v1-2004-Jager
Informational Classifier Fusion (SJ), pp. 216–219.
ICPRICPR-v1-2004-KangD #approximate #bound #fault
Product Approximation by Minimizing the Upper Bound of Bayes Error Rate for Bayesian Combination of Classifiers (HJK, DSD), pp. 252–255.
ICPRICPR-v1-2004-KolschKNP #image
Enhancements for Local Feature Based Image Classification (TK, DK, HN, RP), pp. 248–251.
ICPRICPR-v1-2004-LeydierBE #adaptation #image #segmentation
Serialized Unsupervised Classifier for Adaptative Color Image Segmentation: Application to Digitized Ancient Manuscripts (YL, FLB, HE), pp. 494–497.
ICPRICPR-v1-2004-LiS #design
SVM-Based Classifier Design with Controlled Confidence (ML, IKS), pp. 164–167.
ICPRICPR-v1-2004-LiuM #recognition #string
Handwritten Numeral String Recognition: Character-Level vs. String-Level Classifier Training (CLL, KM), pp. 405–408.
ICPRICPR-v1-2004-Manley-CookeR #fuzzy
A Modified Fuzzy Inference System for Pattern Classification (PMC, MR), pp. 256–259.
ICPRICPR-v1-2004-MansillaH #on the
On Classifier Domains of Competence (EBiM, TKH), pp. 136–139.
ICPRICPR-v1-2004-MilgramSC #modelling
Two-Stage Classification System combining Model-Based and Discriminative Approaches (JM, RS, MC), pp. 152–155.
ICPRICPR-v1-2004-ToselliJV #recognition
Spontaneous Handwriting Recognition and Classification (AHT, AJ, EV), pp. 433–436.
ICPRICPR-v1-2004-VaswaniC #analysis #component #null #probability
Classification Probability Analysis of Principal Component Null Space Analysis (NV, RC), pp. 240–243.
ICPRICPR-v1-2004-WithagenSG #probability
Probabilistic Classification Between Foreground Objects and Background (PJW, KS, FCAG), pp. 31–34.
ICPRICPR-v1-2004-XuC #statistics
Statistical Landscape Features for Texture Classification (CLX, YQC), pp. 676–679.
ICPRICPR-v1-2004-YiKZ #learning
Classifier Combination based on Active Learning (XY, ZK, CZ), pp. 184–187.
ICPRICPR-v1-2004-ZhangP
SVM vs Regularized Least Squares Classification (PZ, JP), pp. 176–179.
ICPRICPR-v1-2004-ZouariHLA #performance #simulation
Simulating Classifier Ensembles of Fixed Diversity for Studying Plurality Voting Performance (HZ, LH, YL, AMA), pp. 232–235.
ICPRICPR-v2-2004-BrownCA #performance #set
Efficient Calculation of the Complete Optimal Classification Set (MB, NC, SA), pp. 307–310.
ICPRICPR-v2-2004-CaoK #online
Online Structure Based Chinese Character Pre-Classification (HC, ACK), pp. 395–398.
ICPRICPR-v2-2004-DeselaersKN #evaluation #fault #image #retrieval
Classification Error Rate for Quantitative Evaluation of Content-based Image Retrieval Systems (TD, DK, HN), pp. 505–508.
ICPRICPR-v2-2004-FarmerJ #approach #image #segmentation
A Wrapper-Based Approach to Image Segmentation and Classification (MEF, AKJ), pp. 106–109.
ICPRICPR-v2-2004-HuR #clustering #probability #using
Probability Table Compression Using Distributional Clustering for Scanning N-Tuple Classifiers (JH, ER), pp. 533–536.
ICPRICPR-v2-2004-IurgelR #documentation #probability #using
Spoken Document Classification with SVMs Using Linguistic Unit Weighting and Probabilistic Couplers (UI, GR), pp. 667–670.
ICPRICPR-v2-2004-KaneS #image #learning #network
Bayesian Network Structure Learning and Inference in Indoor vs. Outdoor Image Classification (MJK, AES), pp. 479–482.
ICPRICPR-v2-2004-LeungNL
ICA-FX Features for Classification of Singing Voice and Instrumental Sound (TWL, CWN, RWHL), pp. 367–370.
ICPRICPR-v2-2004-LillholmP
Jet Based Feature Classification (ML, KSP), pp. 787–790.
ICPRICPR-v2-2004-MaD #adaptation #using #word
Adaptive Word Style Classification Using a Gaussian Mixture Model (HM, DSD), pp. 606–609.
ICPRICPR-v2-2004-MozaffarifK #comparison #recognition #using
Feature Comparison between Fractal Codes and Wavelet Transform in Handwritten Alphanumeric Recognition Using SVM Classifier (SM, KF, HRK), pp. 331–334.
ICPRICPR-v2-2004-PranckevicieneBS #identification
Consensus-Based Identification of Spectral Signatures for Classification of High-Dimensional Biomedical Spectra (EP, RB, RLS), pp. 319–322.
ICPRICPR-v2-2004-Rodriguez-DamianCFS #using
Pollen Classification using Brightness-Based and Shape-Based Descriptors (MRD, EC, AF, PdSO), pp. 212–215.
ICPRICPR-v2-2004-RubeAK #invariant #multi
Coarse-to-Fine Multiscale Affine Invariant Shape Matching and Classification (IER, MA, MK), pp. 163–166.
ICPRICPR-v2-2004-TahirBKA #feature model #using
Feature Selection using Tabu Search for Improving the Classification Rate of Prostate Needle Biopsies (MAT, AB, FK, AA), pp. 335–338.
ICPRICPR-v2-2004-VijayaMS #clustering #performance #sequence
An Efficient Technique for Protein Sequence Clustering and Classification (PAV, MNM, DKS), pp. 447–450.
ICPRICPR-v2-2004-WashizawaY #kernel #pattern matching #pattern recognition #recognition
Kernel Sample Space Projection Classifier for Pattern Recognition (YW, YY), pp. 435–438.
ICPRICPR-v2-2004-XuGSRTW
High Accuracy Classification of EEG Signal (WX, CG, CES, SR, MT, JW), pp. 391–394.
ICPRICPR-v2-2004-YamaguchiM #image
Character Extraction from Natural Scene Images by Hierarchical Classifiers (TY, MM), pp. 687–690.
ICPRICPR-v2-2004-ZhangHHZ #kernel #visual notation
Kernel Autoassociator with Applications to Visual Classification (HZ, WH, ZH, BZ), pp. 443–446.
ICPRICPR-v3-2004-ArchambeauBPVT #parametricity
Supervised Nonparametric Information Theoretic Classification (CA, TB, VP, MV, JPT), pp. 414–417.
ICPRICPR-v3-2004-DEliaMMPST #clustering #detection #segmentation
Detection of Microcalcifications Clusters in Mammograms through TS-MRF Segmentation and SVM-based Classification (CD, CM, MM, GP, GS, FT), pp. 742–745.
ICPRICPR-v3-2004-ForestiMS #automation
Event Classification for Automatic Visual-based Surveillance of Parking Lots (GLF, CM, LS), pp. 314–317.
ICPRICPR-v3-2004-GutkinK #representation #speech
Structural Representation of Speech for Phonetic Classification (AG, SK), pp. 438–441.
ICPRICPR-v3-2004-HolmstromH #estimation
Application of Semiparametric Density Estimation to Classification (LH, FH), pp. 371–374.
ICPRICPR-v3-2004-JainH #component #gender #independence
Integrating Independent Components and Support Vector Machines for Gender Classification (AJ, JH), pp. 558–561.
ICPRICPR-v3-2004-KatoW #algorithm #nearest neighbour #performance
Direct Condensing: An Efficient Voronoi Condensing Algorithm for Nearest Neighbor Classifiers (TK, TW), pp. 474–477.
ICPRICPR-v3-2004-KuhlKWK #using
Training of Classifiers Using Virtual Samples Only (AK, LK, CW, UK), pp. 418–421.
ICPRICPR-v3-2004-LiCKG #detection #image
Detecting Abnormal Regions in Colonoscopic Images by Patch-based Classifier Ensemble (PL, KLC, SMK, YG), pp. 774–777.
ICPRICPR-v3-2004-LiewWY #sequence #statistics
Selection of Statistical Features Based on Mutual Information for Classification of Human Coding and Non-coding DNA Sequences (AWCL, YW, HY), pp. 766–769.
ICPRICPR-v3-2004-PozdnoukhovB #image #invariant #kernel
Tangent Vector Kernels for Invariant Image Classification with SVMs (AP, SB), pp. 486–489.
ICPRICPR-v3-2004-RahtuH #multi
Object Classification with Multi-Scale Autoconvolution (ER, JH), pp. 37–40.
ICPRICPR-v3-2004-ReiterR #multi #programming #segmentation #using
Segmentation and Classification of Meeting Events using Multiple Classifier Fusion and Dynamic Programming (SR, GR), pp. 434–437.
ICPRICPR-v3-2004-ShiNGY #learning
Critical Vector Learning to Construct RBF Classifiers (DS, GSN, JG, DSY), pp. 359–362.
ICPRICPR-v3-2004-SprevakAW #assessment
A Non-Random Data Sampling Method for Classification Model Assessment (DS, FA, HW), pp. 406–409.
ICPRICPR-v3-2004-TaxM
A Consistency-Based Model Selection for One-Class Classification (DMJT, KRM), pp. 363–366.
ICPRICPR-v3-2004-Windeatt #design
Diversity/Accuracy and Ensemble Classifier Design (TW), pp. 454–457.
ICPRICPR-v3-2004-WuAH #image #retrieval
Facial Image Retrieval Based on Demographic Classification (BW, HA, CH), pp. 914–917.
ICPRICPR-v3-2004-ZhouK04a
The Pattern Classification Based on the Nearest Feature Midpoints (ZZ, CKK), pp. 446–449.
ICPRICPR-v4-2004-BoutellL04a #image #metadata
Photo Classification by Integrating Image Content and Camera Metadata (MRB, JL), pp. 901–904.
ICPRICPR-v4-2004-Cardenas #learning #multi #prototype #string
A Learning Model for Multiple-Prototype Classification of Strings (RAM), pp. 420–423.
ICPRICPR-v4-2004-GorgevikC #performance #recognition
An Efficient Three-Stage Classifier for Handwritten Digit Recognition (DG, DC), pp. 507–510.
ICPRICPR-v4-2004-HakeemS #framework #ontology #taxonomy
Ontology and Taxonomy Collaborated Framework for Meeting Classification (AH, MS), pp. 219–222.
ICPRICPR-v4-2004-LimJ #image
Cascading Classifiers for Consumer Image Indexing (JHL, JSJ), pp. 897–900.
ICPRICPR-v4-2004-LiuWLT #recognition
Nearest Intra-Class Space Classifier for Face Recognition (WL, YW, SZL, TT), pp. 495–498.
ICPRICPR-v4-2004-LiuWP #composition #empirical
Texture Classification Through Directional Empirical Mode Decomposition (ZL, HW, SP), pp. 803–806.
ICPRICPR-v4-2004-Moreno-SecoMO #nearest neighbour #rule-based
A New Classification Rule based on Nearest Neighbour Search (FMS, LM, JO), pp. 408–411.
ICPRICPR-v4-2004-MurinoBR #fault #statistics
Statistical Classification of Raw Textile Defects (VM, MB, IAR), pp. 311–314.
ICPRICPR-v4-2004-NandedkarB #architecture #fuzzy #network
A Fuzzy Min-Max Neural Network Classifier with Compensatory Neuron Architecture (AVN, PKB), pp. 553–556.
ICPRICPR-v4-2004-OuMF #multi #network #using
Multiclass Pattern Classification Using Neural Networks (GO, YLM, LAF), pp. 585–588.
ICPRICPR-v4-2004-ShapiroG #multi #recognition #segmentation
Multinational License Plate Recognition System: Segmentation and Classification (VS, GG), pp. 352–355.
ICPRICPR-v4-2004-ShettyR #detection #modelling
An Undecimated Wavelet Transform Based Denoising, PPCA Based Pulse Modeling and Detection-Classification of PD Signals (PKS, TSR), pp. 873–876.
ICPRICPR-v4-2004-UekiKIKISKK #gender #image
A Method of Gender Classification by Integrating Facial, Hairstyle, and Clothing Images (KU, HK, SI, KK, NS, JK, TK), pp. 446–449.
ICPRICPR-v4-2004-ViswanathMB #nearest neighbour #pattern matching #pattern recognition #performance #recognition #synthesis
A Pattern Synthesis Technique with an Efficient Nearest Neighbor Classifier for Binary Pattern Recognition (PV, MNM, SB), pp. 416–419.
KDDKDD-2004-AggarwalHWY #data type #on the
On demand classification of data streams (CCA, JH, JW, PSY), pp. 503–508.
KDDKDD-2004-AksoyKTM #image #interactive #mining
Interactive training of advanced classifiers for mining remote sensing image archives (SA, KK, CT, GBM), pp. 773–782.
KDDKDD-2004-DalviDMSV
Adversarial classification (NND, PMD, M, SKS, DV), pp. 99–108.
KDDKDD-2004-JensenNG #relational #why
Why collective inference improves relational classification (DJ, JN, BG), pp. 593–598.
KDDKDD-2004-LiuYM #algorithm #parametricity #performance
The IOC algorithm: efficient many-class non-parametric classification for high-dimensional data (TL, KY, AWM), pp. 629–634.
KDDKDD-2004-PavlovBDKP #clustering #documentation #multi #naive bayes #preprocessor
Document preprocessing for naive Bayes classification and clustering with mixture of multinomials (DP, RB, BD, SK, JP), pp. 829–834.
KRKR-2004-GrootTH #analysis #approximate #case study #problem #towards
Towards a Structured Analysis of Approximate Problem Solving: A Case Study in Classification (PG, AtT, FvH), pp. 399–406.
KRKR-2004-Pirri
Indoor Environment Classification and Perceptual Matching (FP), pp. 73–84.
SEKESEKE-2004-KhoshgoftaarJ #case study #quality
Noise Elimination with Ensemble-Classifier Filtering: A Case-Study in Software Quality Engineerin (TMK, VHJ), pp. 226–231.
SIGIRSIGIR-2004-AeryC #email #named
eMailSift: mining-based approaches to email classification (MA, SC), pp. 580–581.
SIGIRSIGIR-2004-FanL #semantics #video
Semantic video classification by integrating unlabeled samples for classifier training (JF, HL), pp. 592–593.
SIGIRSIGIR-2004-KumaranA #detection
Text classification and named entities for new event detection (GK, JA), pp. 297–304.
SIGIRSIGIR-2004-MladenicBGM #feature model #interactive #linear #modelling #using
Feature selection using linear classifier weights: interaction with classification models (DM, JB, MG, NMF), pp. 234–241.
SIGIRSIGIR-2004-ShenCYZZLM #summary
Web-page classification through summarization (DS, ZC, QY, HJZ, BZ, YL, WYM), pp. 242–249.
SIGIRSIGIR-2004-YangC #effectiveness #web
Effectiveness of web page classification on finding list answers (HY, TSC), pp. 522–523.
SIGIRSIGIR-2004-Zhang #adaptation #using
Using bayesian priors to combine classifiers for adaptive filtering (YZ0), pp. 345–352.
UMLUML-2004-JiangSZMMM #metamodelling #on the #uml
On the Classification of UML’s Meta Model Extension Mechanism (YJ, WS, LZ, ZM, XM, HM), pp. 54–68.
FSEFSE-2004-RinardSB #analysis #aspect-oriented #source code
A classification system and analysis for aspect-oriented programs (MCR, AS, SB), pp. 147–158.
SACSAC-2004-BaralisCG #on the
On support thresholds in associative classification (EB, SC, PG), pp. 553–558.
SACSAC-2004-BeneventanoM #framework
A framework for the classification and the reclassification of electronic catalogs (DB, SM), pp. 784–788.
SACSAC-2004-DamianiDG #multi #thread
Re-classification and multi-threading: FickleMT (FD, MDC, PG), pp. 1297–1304.
SACSAC-2004-EggermontKK #clustering #programming #search-based
Genetic Programming for data classification: partitioning the search space (JE, JNK, WAK), pp. 1001–1005.
SACSAC-2004-ZhouL #network
Regularized B-spline network and its application to heart arrhythmia classification (JZ, LL), pp. 291–295.
SACSAC-PL-J-2004-DamianiDG #multi #on the #thread
On Re-classification and Multi-threading (FD, MDC, PG), pp. 5–30.
OSDIOSDI-2004-GniadyBH
Program-Counter-Based Pattern Classification in Buffer Caching (CG, ARB, YCH), pp. 395–408.
ESOPESOP-2004-CalcagnoMT
ML-Like Inference for Classifiers (CC, EM, WT), pp. 79–93.
IJCARIJCAR-2004-ColtonMSM #algebra #automation #finite #generative #theorem
Automatic Generation of Classification Theorems for Finite Algebras (SC, AM, VS, RLM), pp. 400–414.
DocEngDocEng-2003-DenoyerVGBB #documentation #multi
Structured multimedia document classification (LD, JNV, PG, SB, SB), pp. 153–160.
DocEngDocEng-2003-ZuOWK #automation
Accuracy improvement of automatic text classification based on feature transformation (GZ, WO, TW, FK), pp. 118–120.
DRRDRR-2003-Summers #documentation #image #problem
Document image improvment for OCR as a classification problem (KMS), pp. 73–83.
TPDLECDL-2003-FerilliEBM #automation #induction
Automatic Induction of Rules for Classification and Interpretation of Cultural Heritage Material (SF, FE, TMAB, NDM), pp. 152–163.
ICDARICDAR-2003-BaldiMS #set #using
Using tree-grammars for training set expansion in page classification (SB, SM, GS), pp. 829–833.
ICDARICDAR-2003-Biem #optimisation
A Model Selection Criterion for Classification: Application to HMM Topology Optimization (AB), pp. 104–108.
ICDARICDAR-2003-EglinB #documentation #layout #query #similarity #visual notation
Document page similarity based on layout visual saliency: Application to query by example and document classification (VE, SB), pp. 1208–1212.
ICDARICDAR-2003-FutrelleSCG #analysis #diagrams #documentation #layout
Extraction, layout analysis and classification of diagrams in PDF documents (RPF, MS, CC, AEG), pp. 1007–1014.
ICDARICDAR-2003-GocciaBSD #feature model #optimisation #recognition
Recognition of Container Code Characters through Gray-Level Feature Extraction and Gradient-Based Classifier Optimization (MG, MB, CS, SGD), p. 973–?.
ICDARICDAR-2003-GuestCFP #analysis #automation #geometry #sequence #using
Automatic Classification of Hand Drawn Geometric Shapes using Constructional Sequence Analysis (RMG, SC, MCF, JMP), pp. 990–994.
ICDARICDAR-2003-HamamuraMI #multi
A Multiclass Classification Method Based on Multiple Pairwise Classifiers (TH, HM, BI), pp. 809–813.
ICDARICDAR-2003-HaoLS #evaluation
Confidence Evaluation for Combining Diverse Classifiers (HH, CLL, HS), pp. 760–764.
ICDARICDAR-2003-HaoLS03a #algorithm #comparison #search-based #set
Comparison of Genetic Algorithm and Sequential Search Methods for Classifier Subset Selection (HH, CLL, HS), pp. 765–769.
ICDARICDAR-2003-HoqueSF #approach #multi #performance #recognition
A New Chain-code Quantization Approach Enabling High Performance Handwriting Recognition based on Multi-Classifier Schemes (SH, KS, MCF), pp. 834–838.
ICDARICDAR-2003-KangD #dependence #higher-order #multi
Combining Multiple Classifiers based on Third-Order Dependency (HJK, DSD), pp. 21–25.
ICDARICDAR-2003-KangD03a #evaluation #multi
Evaluation of the Information-Theoretic Construction of Multiple Classifier Systems (HJK, DSD), pp. 789–793.
ICDARICDAR-2003-KimMO #algorithm #statistics #word
A Text Watermarking Algorithm based on Word Classification and Inter-word Space Statistics (YWK, KAM, ISO), pp. 775–779.
ICDARICDAR-2003-LeeO #multi #problem
Binary Classification Trees for Multi-class Classification Problems (JSL, ISO), pp. 770–774.
ICDARICDAR-2003-MaD #documentation #image #multi
Gabor Filter Based Multi-class Classifier for Scanned Document Images (HM, DSD), pp. 968–972.
ICDARICDAR-2003-PrevostMMOM #modelling #recognition
Combining model-based and discriminative classifiers : application to handwritten character recognition (LP, CMS, AM, LO, MM), p. 31–?.
ICDARICDAR-2003-RagotA #fuzzy #hybrid #modelling #online #recognition
A Generic Hybrid Classifier Based on Hierarchical Fuzzy Modeling: Experiments on On-Line Handwritten Character Recognition (NR, ÉA), pp. 963–967.
ICDARICDAR-2003-SchenkerLBK #documentation #graph #using #web
Classification of Web Documents Using a Graph Model (AS, ML, HB, AK), pp. 240–244.
ICDARICDAR-2003-StefanoCM #algorithm #reliability #search-based
Exploiting Reliability for Dynamic Selection of Classifiers by Means of Genetic Algorithms (CDS, ADC, AM), pp. 671–675.
ICDARICDAR-2003-VelekN #online #performance #recognition #scalability #set
Enhancing Efficiency and Speed of an Off-line Classifier Employed for On-line Handwriting Recognition of a Large Character Set (OV, MN), pp. 784–788.
ICDARICDAR-2003-YamaguchiNMMH #recognition
Digit Classification on Signboards for Telephone Number Recognition (TY, YN, MM, HM, TH), pp. 359–363.
ICDARICDAR-2003-ZouariHLA #parallel
A New Classifier Simulator for Evaluating Parallel Combination Methods (HZ, LH, YL, AMA), pp. 26–30.
SIGMODSIGMOD-2003-FaginKS #performance #rank #similarity
Efficient similarity search and classification via rank aggregation (RF, RK, DS), pp. 301–312.
ICSMEICSM-2003-Gustavsson #java #runtime
A Classification of Unanticipated Runtime Software Changes in Java (JG), pp. 4–12.
ICEISICEIS-v2-2003-HassanienA #algorithm #image #performance #retrieval #set
An Efficient Classification and Image Retrieval Algorithm Based on Rough Set Theory (AEH, JMHA), pp. 457–460.
ICEISICEIS-v2-2003-TungFB #information management
Knowledge Management and Data Classification in Pellucid (TTD, BF, IB), pp. 209–216.
ICEISICEIS-v3-2003-ToffolonD03a #prototype
Software Prototyping Classification (CT, SD), pp. 266–271.
ICEISICEIS-v4-2003-PlaisentOBM #internet #towards
Toward a Classification of Internet Scientific Conferences (MP, AO, PB, LM), pp. 473–476.
CIKMCIKM-2003-AdamiAS #documentation
Bootstrapping for hierarchical document classification (GA, PA, DS), pp. 295–302.
CIKMCIKM-2003-CaladoCMZRG #documentation #web
Combining link-based and content-based methods for web document classification (PC, MC, ESdM, NZ, BARN, MAG), pp. 394–401.
CIKMCIKM-2003-KaoQPW #information management
User assisted text classification and knowledge management (AK, LQ, SP, SW), pp. 524–527.
CIKMCIKM-2003-MacskassyH
Adding numbers to text classification (SAM, HH), pp. 240–246.
CIKMCIKM-2003-ShanahanR
Boosting support vector machines for text classification through parameter-free threshold relaxation (JGS, NR), pp. 247–254.
CIKMCIKM-2003-YuZH #documentation
Text classification from positive and unlabeled documents (HY, CZ, JH), pp. 232–239.
ECIRECIR-2003-CeciM #documentation #html
Hierarchical Classification of HTML Documents with WebClassII (MC, DM), pp. 57–72.
ECIRECIR-2003-FisherE
When Are Links Useful? Experiments in Text Classification (MF, RME), pp. 41–56.
ECIRECIR-2003-Moschitti #case study #parametricity
A Study on Optimal Parameter Tuning for Rocchio Text Classifier (AM), pp. 420–435.
ECIRECIR-2003-PengS #modelling #n-gram #naive bayes
Combining Naive Bayes and n-Gram Language Models for Text Classification (FP, DS), pp. 335–350.
ECIRECIR-2003-XuYTXW #using
Representative Sampling for Text Classification Using Support Vector Machines (ZX, KY, VT, XX, JW), pp. 393–407.
ICMLICML-2003-DeCosteM #approximate #incremental #kernel #performance
Fast Query-Optimized Kernel Machine Classification Via Incremental Approximate Nearest Support Vectors (DD, DM), pp. 115–122.
ICMLICML-2003-Jaeger #concept #probability
Probabilistic Classifiers and the Concepts They Recognize (MJ), pp. 266–273.
ICMLICML-2003-KlautauJO #comparison #kernel #modelling
Discriminative Gaussian Mixture Models: A Comparison with Kernel Classifiers (AK, NJ, AO), pp. 353–360.
ICMLICML-2003-KrishnapuramCJ #documentation
Classification of Text Documents Based on Minimum System Entropy (RK, KPC, SJ), pp. 384–391.
ICMLICML-2003-LachicheF #multi #probability #using
Improving Accuracy and Cost of Two-class and Multi-class Probabilistic Classifiers Using ROC Curves (NL, PAF), pp. 416–423.
ICMLICML-2003-LagoudakisP #learning
Reinforcement Learning as Classification: Leveraging Modern Classifiers (MGL, RP), pp. 424–431.
ICMLICML-2003-LiWL #generative #keyword #probability #using
Text Classification Using Stochastic Keyword Generation (CL, JRW, HL), pp. 464–471.
ICMLICML-2003-LiY #analysis #categorisation
A Loss Function Analysis for Classification Methods in Text Categorization (FL, YY), pp. 472–479.
ICMLICML-2003-LuG
Link-based Classification (QL, LG), pp. 496–503.
ICMLICML-2003-PorterEHT #order #scalability #statistics
Weighted Order Statistic Classifiers with Large Rank-Order Margin (RBP, DE, DRH, JT), pp. 600–607.
ICMLICML-2003-RennieSTK #naive bayes
Tackling the Poor Assumptions of Naive Bayes Text Classifiers (JDR, LS, JT, DRK), pp. 616–623.
ICMLICML-2003-RosipalTM #kernel #linear
Kernel PLS-SVC for Linear and Nonlinear Classification (RR, LJT, BM), pp. 640–647.
ICMLICML-2003-YanDMW #approximate #optimisation #performance #statistics
Optimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic (LY, RHD, MM, RHW), pp. 848–855.
KDDKDD-2003-BhatnagarKN #mining
Mining high dimensional data for classifier knowledge (RB, GK, WN), pp. 481–486.
KDDKDD-2003-WangFYH #concept #data type #mining #using
Mining concept-drifting data streams using ensemble classifiers (HW, WF, PSY, JH), pp. 226–235.
KDDKDD-2003-ZakiA #effectiveness #named #xml
XRules: an effective structural classifier for XML data (MJZ, CCA), pp. 316–325.
MLDMMLDM-2003-BouguilaZV #image #novel
Novel Mixtures Based on the Dirichlet Distribution: Application to Data and Image Classification (NB, DZ, JV), pp. 172–181.
MLDMMLDM-2003-EstruchFHR
Simple Mimetic Classifiers (VE, CF, JHO, MJRQ), pp. 156–171.
MLDMMLDM-2003-KuhnertK #image #learning
A Learning Autonomous Driver System on the Basis of Image Classification and Evolutional Learning (KDK, MK), pp. 400–412.
MLDMMLDM-2003-MiteranBB #approximate #bound #image #realtime #segmentation #using
Classification Boundary Approximation by Using Combination of Training Steps for Real-Time Image Segmentation (JM, SB, EBB), pp. 141–155.
MLDMMLDM-2003-Scaringella #on the
On the Size of a Classification Tree (AS), pp. 65–72.
SIGIRSIGIR-2003-Bennett #probability #symmetry #using
Using asymmetric distributions to improve text classifier probability estimates (PNB), pp. 111–118.
SIGIRSIGIR-2003-HanMGZ #clustering #rule-based #word
Rule-based word clustering for text classification (HH, EM, CLG, HZ), pp. 445–446.
SIGIRSIGIR-2003-KangK #documentation #query #retrieval #web
Query type classification for web document retrieval (IHK, GCK), pp. 64–71.
SIGIRSIGIR-2003-KrovetzUG #source code
Classification of source code archives (RK, SU, CLG), pp. 425–426.
SIGIRSIGIR-2003-LiOL #case study #comparative #music
A comparative study on content-based music genre classification (TL, MO, QL), pp. 282–289.
SIGIRSIGIR-2003-TsaiMT #hybrid #image #network #using
Image classification using hybrid neural networks (CFT, KM, JT), pp. 431–432.
SIGIRSIGIR-2003-YangZK #analysis #categorisation #scalability
A scalability analysis of classifiers in text categorization (YY, JZ, BK), pp. 96–103.
SIGIRSIGIR-2003-ZhangL #using
Question classification using support vector machines (DZ, WSL), pp. 26–32.
SIGIRSIGIR-2003-ZhangY #categorisation #linear #robust
Robustness of regularized linear classification methods in text categorization (JZ, YY), pp. 190–197.
POPLPOPL-2003-TahaN
Environment classifiers (WT, MFN), pp. 26–37.
SACSAC-2003-LiZLO #functional #learning #semistructured data
Gene Functional Classification by Semisupervised Learning from Heterogeneous Data (TL, SZ, QL, MO), pp. 78–82.
SACSAC-2003-NenkovaB #email
Email Classification for Contact Centers (AN, AB), pp. 789–792.
SACSAC-2003-WangBD #approach
A Density Based Approach to Classification (HW, DAB, ID), pp. 470–474.
SACSAC-2003-WombacherMR #ad hoc #modelling #multi #workflow
Classification of Ad hoc Multi-lateral Collaborations Based on Local Workflow Models (AW, BM, TR), pp. 1185–1190.
SACSAC-2003-YangH #data flow #image #using
Image Texture Classification Using Datagrams and Characteristic Views (SY, CCH), pp. 22–26.
SACSAC-2003-YuNPC #on the #testing #using
On the Use of the Classification-Tree Method by Beginning Software Testers (YTY, SPN, PLP, TYC), pp. 1123–1127.
DATEDATE-2003-CorsiMM #approach #pseudo #random testing #testing
An Approach to the Classification of Mixed-Signal Circuits in a Pseudorandom Testing Scheme (FC, CM, GM), pp. 11178–11179.
TPDLECDL-2002-GreenbergBJDW #comprehension #education #library #student
Student Comprehension of Classification Applications in a Science Education Digital Library (JG, KAB, MLJ, ED, PW), pp. 560–567.
TPDLECDL-2002-SunLN #keyword #personalisation
Personalized Classification for Keyword-Based Category Profiles (AS, EPL, WKN), pp. 61–74.
JCDLJCDL-2002-CuiHZ #approach #automation #information retrieval
An approach to automatic classification of text for information retrieval (HC, PBH, HZ), pp. 96–97.
JCDLJCDL-2002-TudhopeBBC
Compound descriptors in context: a matching function for classifications and thesauri (DT, CB, DB, DC), pp. 84–93.
VLDBVLDB-2002-ChakrabartiRS #linear #multi #performance
Fast and Accurate Text Classification via Multiple Linear Discriminant Projections (SC, SR, MVS), pp. 658–669.
FMFME-2002-HendersonP #communication #verification
The Formal Classification and Verification of Simpson’s 4-Slot Asynchronous Communication Mechanism (NH, SP), pp. 350–369.
ICEISICEIS-2002-SantosNASR #data mining #database #learning #mining #using
Augmented Data Mining over Clinical Databases Using Learning Classifier Systems (MFS, JN, AA, ÁMS, FR), pp. 512–516.
ICEISICEIS-2002-Veryha #database #fuzzy #implementation #query #relational #using
Implementation of Fuzzy Classification Query Language in Relational Databases Using Stored Procedures (YV), pp. 195–202.
CIKMCIKM-2002-DeshpandeK #using
Using conjunction of attribute values for classification (MD, GK), pp. 356–364.
CIKMCIKM-2002-LiuH #identification #music
A singer identification technique for content-based classification of MP3 music objects (CCL, CSH), pp. 438–445.
CIKMCIKM-2002-LiuYC #bias #induction
Boosting to correct inductive bias in text classification (YL, YY, JGC), pp. 348–355.
CIKMCIKM-2002-RogatiY #feature model
High-performing feature selection for text classification (MR, YY), pp. 659–661.
CIKMCIKM-2002-StehlingNF #approach #image #performance #retrieval
A compact and efficient image retrieval approach based on border/interior pixel classification (ROS, MAN, AXF), pp. 102–109.
ECIRECIR-2002-FinnKS #information management
Genre Classification and Domain Transfer for Information Filtering (AF, NK, BS), pp. 353–362.
ICMLICML-2002-DashC #naive bayes
Exact model averaging with naive Bayesian classifiers (DD, GFC), pp. 91–98.
ICMLICML-2002-DeCoste #distance #geometry #kernel #performance
Anytime Interval-Valued Outputs for Kernel Machines: Fast Support Vector Machine Classification via Distance Geometry (DD), pp. 99–106.
ICMLICML-2002-DzeroskiZ
Is Combining Classifiers Better than Selecting the Best One (SD, BZ), pp. 123–130.
ICMLICML-2002-Ho
Classification Value Grouping (CKMH), pp. 251–258.
ICMLICML-2002-LiuLYL #documentation
Partially Supervised Classification of Text Documents (BL, WSL, PSY, XL), pp. 387–394.
ICMLICML-2002-RaskuttiFK #clustering #parametricity #using
Using Unlabelled Data for Text Classification through Addition of Cluster Parameters (BR, HLF, AK), pp. 514–521.
ICMLICML-2002-ThamDR #learning #markov #monte carlo #using
Sparse Bayesian Learning for Regression and Classification using Markov Chain Monte Carlo (SST, AD, KR), pp. 634–641.
ICMLICML-2002-Ting #evaluation #using
Issues in Classifier Evaluation using Optimal Cost Curves (KMT), pp. 642–649.
ICMLICML-2002-YangW
Non-Disjoint Discretization for Naive-Bayes Classifiers (YY, GIW), pp. 666–673.
ICPRICPR-v1-2002-ArlandisPC #metric
Rejection Strategies and Confidence Measures for a k- NN Classifier in an OCR Task (JA, JCPC, JCP), pp. 576–579.
ICPRICPR-v1-2002-Baggenstoss
The Chain-Rule Processor: Optimal Classification Through Signal Processing (PMB), pp. 230–234.
ICPRICPR-v1-2002-ClaudeWPB #image #network
Contour Features for Colposcopic Image Classification by Artificial Neural Networks (IC, RW, PP, JCB), pp. 771–774.
ICPRICPR-v1-2002-DuchesneBBC #image #on the #using
On the Classification of Temporal Lobe Epilepsy Using MR Image Appearance (SD, NB, AB, DLC), pp. 520–523.
ICPRICPR-v1-2002-KampelS #automation #segmentation
Automated Segmentation of Archaeological Profiles or Classification (MK, RS), pp. 57–60.
ICPRICPR-v1-2002-LiuS #recognition #representation
A Spectral Representation for Appearance-Based Classification and Recognition (XL, AS), pp. 37–40.
ICPRICPR-v1-2002-SebeLCGH #naive bayes #recognition #using
Emotion Recognition Using a Cauchy Naive Bayes Classifier (NS, MSL, IC, AG, TSH), p. 17–?.
ICPRICPR-v1-2002-Souafi-BensafiPLE #documentation #network
Bayesian Networks Classifiers Applied to Documents (SSB, MP, FL, HE), p. 483–?.
ICPRICPR-v1-2002-Torkkola #documentation
Discriminative Features for Document Classification (KT), pp. 472–475.
ICPRICPR-v1-2002-ZhangD #fault #recognition
Minimum Classification Error Training for Handwritten Character Recognition (RZ, XD), pp. 580–583.
ICPRICPR-v1-2002-ZhuY #documentation
A New Textual/Non-Textual Classifier for Document Skew Correction (XZ, XY), pp. 480–482.
ICPRICPR-v2-2002-AksoyH #framework #image #retrieval
A Classification Framework for Content-Based Image Retrieval (SA, RMH), pp. 503–506.
ICPRICPR-v2-2002-AltyncayD #multi #normalisation #problem #question #why
Why Does Output Normalization Create Problems in Multiple Classifier Systems? (HA, MD), pp. 775–778.
ICPRICPR-v2-2002-BalthasarP #performance
Fast Projection Plane Classifier (DB, LP), pp. 200–203.
ICPRICPR-v2-2002-BarataP #clustering #modelling #set #using
Improving Classification Rates by Modelling the Clusters of Trainings Sets in Features Space Using Mathematical Morphology Operators (TB, PP), pp. 328–331.
ICPRICPR-v2-2002-ChoCWS #adaptation #data type #image #learning #representation #robust
Robust Learning in Adaptive Processing of Data Structures for Tree Representation Based Image Classification (SYC, ZC, ZW, WCS), pp. 108–111.
ICPRICPR-v2-2002-Duin #question
The Combining Classifier: To Train or Not to Train? (RPWD), pp. 765–770.
ICPRICPR-v2-2002-ErcilB #polynomial #using
One Class Classification Using Implicit Polynomial Surface Fitting (AE, BB), pp. 152–155.
ICPRICPR-v2-2002-FrantiX #using
Classification of Binary Vectors by Using ??SC-Distance (PF, MX), pp. 52–55.
ICPRICPR-v2-2002-GargPH #network
Bayesian Networks as Ensemble of Classifiers (AG, VP, TSH), pp. 779–784.
ICPRICPR-v2-2002-GiacintoR #detection #multi #network
Intrusion Detection in Computer Networks by Multiple Classifier Systems (GG, FR), pp. 390–393.
ICPRICPR-v2-2002-GuillametSV #image #matrix
Analyzing Non-Negative Matrix Factorization for Image Classification (DG, BS, JV), pp. 116–119.
ICPRICPR-v2-2002-GuptaDD #automation #fault #feature model
Beam Search for Feature Selection in Automatic SVM Defect Classification (PG, DSD, DD), pp. 212–215.
ICPRICPR-v2-2002-GuunterB #recognition
A New Combination Scheme for HMM-Based Classififiers and its Application to Handwriting Recognition (SG, HB), pp. 332–337.
ICPRICPR-v2-2002-Han #using
A Supervised Classification Scheme Using Positive Boolean Function (CCH), pp. 100–103.
ICPRICPR-v2-2002-HuangT #fault #pattern matching #pattern recognition #recognition
An RBF-Based Pattern Recognition Method by Competitively Reducing Classification-Oriented Error (YSH, YHT), pp. 180–183.
ICPRICPR-v2-2002-HungYL #image #using
Use of Characteristic Views in Image Classification (CCH, SY, CML), pp. 949–952.
ICPRICPR-v2-2002-JainM #kernel
Hierarchical Kernel Fitting for Fingerprint Classification and Alignment (AKJ, SM), pp. 469–473.
ICPRICPR-v2-2002-KimPJKB #using
Pattern Classification Using Support Vector Machine Ensemble (HCK, SP, HMJ, DK, SYB), pp. 160–163.
ICPRICPR-v2-2002-LoogG #segmentation
Supervised Segmentation by Iterated Contextual Pixel Classification (ML, BvG), pp. 925–928.
ICPRICPR-v2-2002-MesserCK #automation
Automatic Sports Classification (KM, WJC, JK), pp. 1005–1008.
ICPRICPR-v2-2002-MurpheyL #feature model #multi #network
Feature Extraction for a Multiple Pattern Classification Neural Network System (YLM, YL), pp. 220–223.
ICPRICPR-v2-2002-Paletta #detection #using
Detection of Traffic Signs Using Posterior Classifier Combination (LP), pp. 705–708.
ICPRICPR-v2-2002-PernerPM
Texture Classification Based on the Boolean Model and its Application to Hep-2 Cells (PP, HP, BM), pp. 406–409.
ICPRICPR-v2-2002-RasheedS
Movie Genre Classification By Exploiting Audio-Visual Features Of Previews (ZR, MS), pp. 1086–1089.
ICPRICPR-v2-2002-RidderPD #complexity #fault
The Economics of Classification: Error vs. Complexity (DdR, EP, RPWD), pp. 244–247.
ICPRICPR-v2-2002-RoliFV #analysis #trade-off
Analysis of Error-Reject Trade-off in Linearly Combined Classifiers (FR, GF, GV), pp. 120–125.
ICPRICPR-v2-2002-RonnebergerBS #3d #invariant #recognition #set #using
General-Purpose Object Recognition in 3D Volume Data Sets Using Gray-Scale Invariants --- Classification of Airborne Pollen-Grains Recorded with a Confocal Laser Scanning Microscope (OR, HB, ES), p. 290–?.
ICPRICPR-v2-2002-RyazanovV #approach #automation #scalability
Discrete Approach for Automatic Knowledge Extraction from Precedent Large-Scale Data, and Classification (VVR, VAV), pp. 188–191.
ICPRICPR-v2-2002-Schiele #how #question
How Many Classifiers Do I Need? (BS), pp. 176–179.
ICPRICPR-v2-2002-SirlantzisFG #algorithm #multi
An Evolutionary Algorithm for Classifier and Combination Rule Selection in Multiple Classifier Systems (KS, MCF, RMG), pp. 771–774.
ICPRICPR-v2-2002-StefanoCM #adaptation #multi
An Adaptive Weighted Majority Vote Rule for Combining Multiple Classifiers (CDS, ADC, AM), pp. 192–195.
ICPRICPR-v2-2002-TassoneWV
Temporal PDMs for Gait Classification (ET, GAWW, SV), pp. 1065–1068.
ICPRICPR-v2-2002-TaxD #multi #using
Using Two-Class Classifiers for Multiclass Classification (DMJT, RPWD), pp. 124–127.
ICPRICPR-v2-2002-Vaswani #linear #matrix
A Linear Classifier for Gaussian Class Conditional Distributions with Unequal Covariance Matrices (NV), pp. 60–63.
ICPRICPR-v2-2002-VeeramachaneniFLN #polynomial
Style-Conscious Quadratic Field Classifier (SV, HF, CLL, GN), pp. 72–75.
ICPRICPR-v3-2002-BaesensECV #learning #markov #monte carlo #network #using
Learning Bayesian Network Classifiers for Credit Scoring Using Markov Chain Monte Carlo Search (BB, MEP, RC, JV), pp. 49–52.
ICPRICPR-v3-2002-BurschkaH
Scene Classification from Dense Disparity Maps in Indoor Environments (DB, GDH), pp. 708–712.
ICPRICPR-v3-2002-GorgevikC #recognition
Combining SVM Classifiers for Handwritten Digit Recognition (DG, DC), pp. 102–105.
ICPRICPR-v3-2002-HoqueFG #learning #performance
The Effect of the Inhibition-Compensation Learning Scheme on n-tuple Based Classifier Performance (SH, MCF, RMG), pp. 452–455.
ICPRICPR-v3-2002-KuritaTI #image #network
A Neural Network Classifier for Occluded Images (TK, TT, YI), pp. 45–48.
ICPRICPR-v3-2002-Kwon #clustering #using
Hangul Tree Classifier for Type Clustering Using Horizontal and Vertical Strokes (YBK), pp. 228–231.
ICPRICPR-v3-2002-LefevreMV #process #segmentation
A Two Level Classifier Process for Audio Segmentation (SL, BM, NV), pp. 891–894.
ICPRICPR-v3-2002-LiangDMG #logic
Page Classification through Logical Labelling (JL, DSD, MYM, JKG), pp. 477–480.
ICPRICPR-v3-2002-PengHD #adaptation #kernel #metric #nearest neighbour
Adaptive Kernel Metric Nearest Neighbor Classification (JP, DRH, HKD), pp. 33–36.
ICPRICPR-v3-2002-QiP
Context-Sensitive Bayesian Classifiers and Application to Mouse Pressure Pattern Classification (Y(Q, RWP), pp. 448–451.
ICPRICPR-v3-2002-RivlinRGBL #realtime
A Real-Time System for Classification of Moving Objects (ER, MR, RG, UB, SL), pp. 688–691.
ICPRICPR-v3-2002-RodriguezSAP #incremental
An Incremental and Hierarchical K-NN Classifier for Handwritten Characters (CR, FBS, ISA, AP), pp. 98–101.
ICPRICPR-v3-2002-SahbiB #detection
Coarse-to-Fine Support Vector Classifiers for Face Detection (HS, NB), pp. 359–362.
ICPRICPR-v3-2002-SiggelkowB #image #retrieval
Improvement of Histogram-Based Image Retrieval and Classification (SS, HB), pp. 367–370.
ICPRICPR-v3-2002-SilvestreL #bound #optimisation
Optimization of Neural Classifiers Based on Bayesian Decision Boundaries and Idle Neurons Pruning (MRS, LLL), pp. 387–390.
ICPRICPR-v3-2002-WangBR #recognition #word
Combining HMM-Based Two-Pass Classifiers for Off-Line Word Recognition (WW, AB, GR), pp. 151–154.
ICPRICPR-v3-2002-WangCZ #automation #documentation #image
Hierarchical Content Classification and Script Determination for Automatic Document Image Processing (QW, ZC, RZ), pp. 77–80.
ICPRICPR-v3-2002-WangPH #documentation
A Method for Document Zone Content Classification (YW, ITP, RMH), p. 196–?.
ICPRICPR-v3-2002-XueG #performance #predict #word
Performance Prediction for Handwritten Word Recognizers and Its Application to Classifier Combination (HX, VG), pp. 241–244.
ICPRICPR-v3-2002-Yang
Extended Isomap for Classification (MHY), pp. 615–618.
ICPRICPR-v4-2002-BarataP02a #clustering #modelling #set #using
Improving Classification Rates by Modelling the Clusters of Trainings Sets in Features Space Using Mathematical Morphology Operators (TB, PP), pp. 90–93.
ICPRICPR-v4-2002-CaputoN #kernel
To Each According to its Need: Kernel Class Specific Classifiers (BC, HN), pp. 94–97.
ICPRICPR-v4-2002-HoogsCK #3d #metaprogramming #using
Classification of 3D Macro Texture Using Perceptual Observables (AH, RC, RK), pp. 113–117.
ICPRICPR-v4-2002-LiuSF #learning #polynomial
Learning Quadratic Discriminant Function for Handwritten Character Classification (CLL, HS, HF), pp. 44–47.
ICPRICPR-v4-2002-MathisB #approach #using
Classification Using a Hierarchical Bayesian Approach (CM, TMB), p. 103–?.
ICPRICPR-v4-2002-MottlKK #identification #kernel
Support Object Classifiers with Rigid and Elastic Kernel Functions for Face Identification (VM, AK, JK), pp. 205–208.
ICPRICPR-v4-2002-PerisM #distance #edit distance #performance
Fast Cyclic Edit Distance Computation with Weighted Edit Costs in Classification (GP, AM), pp. 184–187.
ICPRICPR-v4-2002-Sarkar #algorithm
An Iterative Algorithm for Optimal Style Conscious Field Classification (PS), p. 243–?.
ICPRICPR-v4-2002-SerranoSL #approach #performance
A Computationally Efficient Approach to Indoor/Outdoor Scene Classification (NS, AES, JL), p. 146–?.
ICPRICPR-v4-2002-TothCA #fault
A Two-Stage-Classifier for Defect Classification in Optical Media Inspection (DT, AC, TA), pp. 373–376.
KDDKDD-2002-Aggarwal #effectiveness #on the #string
On effective classification of strings with wavelets (CCA), pp. 163–172.
KDDKDD-2002-DhillonMK #clustering #word
Enhanced word clustering for hierarchical text classification (ISD, SM, RK), pp. 191–200.
KDDKDD-2002-FragoudisML
Integrating feature and instance selection for text classification (DF, DM, SL), pp. 501–506.
KDDKDD-2002-KolczSK #performance #random
Efficient handling of high-dimensional feature spaces by randomized classifier ensembles (AK, XS, JKK), pp. 307–313.
KDDKDD-2002-KruengkraiJ #algorithm #learning #parallel
A parallel learning algorithm for text classification (CK, CJ), pp. 201–206.
KDDKDD-2002-LiB #algorithm
Instability of decision tree classification algorithms (RHL, GGB), pp. 570–575.
KDDKDD-2002-LiTS #robust #set
Construct robust rule sets for classification (JL, RWT, HS), pp. 564–569.
KDDKDD-2002-LiuL #adaptation #documentation #incremental #mining
Incremental context mining for adaptive document classification (RLL, YLL), pp. 599–604.
KDDKDD-2002-Olecka #performance
Evaluating classifiers’ performance in a constrained environment (AO), pp. 605–612.
KDDKDD-2002-RaskuttiFK #clustering #using
Combining clustering and co-training to enhance text classification using unlabelled data (BR, HLF, AK), pp. 620–625.
KDDKDD-2002-UgurelKG #automation #source code #what
What’s the code?: automatic classification of source code archives (SU, RK, CLG), pp. 639–644.
KDDKDD-2002-VlachosDGKK #reduction #visualisation
Non-linear dimensionality reduction techniques for classification and visualization (MV, CD, DG, GK, NK), pp. 645–651.
KDDKDD-2002-WuFS #approach #data mining #mining #named
B-EM: a classifier incorporating bootstrap with EM approach for data mining (XW, JF, KRS), pp. 670–675.
KDDKDD-2002-YuHC #learning #named #using #web
PEBL: positive example based learning for Web page classification using SVM (HY, JH, KCCC), pp. 239–248.
KDDKDD-2002-ZadroznyE #multi #probability
Transforming classifier scores into accurate multiclass probability estimates (BZ, CE), pp. 694–699.
SEKESEKE-2002-Morasca #using
A proposal for using continuous attributes in classification trees (SM), pp. 417–424.
SEKESEKE-2002-NakkrasaeS #approach #component #formal method #specification
A formal approach for specification and classification of software components (SN, PS), pp. 773–780.
SIGIRSIGIR-2002-BennettDH #modelling #probability #reliability #using
Probabilistic combination of text classifiers using reliability indicators: models and results (PNB, STD, EH), pp. 207–214.
SIGIRSIGIR-2002-Boyapati #using
Improving hierarchical text classification using unlabeled data (VB), pp. 363–364.
SIGIRSIGIR-2002-ChaiCN #online
Bayesian online classifiers for text classification and filtering (KMAC, HLC, HTN), pp. 97–104.
SIGIRSIGIR-2002-HardySSTZW #concept #summary
Cross-document summarization by concept classification (HH, NS, TS, TL, XZ, GBW), pp. 121–128.
SIGIRSIGIR-2002-KimRL #estimation #multi #naive bayes #parametricity
A new method of parameter estimation for multinomial naive bayes text classifiers (SBK, HCR, HSL), pp. 391–392.
SIGIRSIGIR-2002-KouG #algorithm
Study of category score algorithms for k-NN classifier (HK, GG), pp. 393–394.
SIGIRSIGIR-2002-LeeM
Text genre classification with genre-revealing and subject-revealing features (YBL, SHM), pp. 145–150.
SIGIRSIGIR-2002-SlonimFT #documentation #using
Unsupervised document classification using sequential information maximization (NS, NF, NT), pp. 129–136.
SIGIRSIGIR-2002-Wolin #automation
Automatic classification in product catalogs (BW), pp. 351–352.
PLDIPLDI-2002-BurtscherDH #predict
Static Load Classification for Improving the Value Predictability of Data-Cache Misses (MB, AD, MH), pp. 222–233.
SACSAC-2002-CrescenziMM #web
Wrapping-oriented classification of web pages (VC, GM, PM), pp. 1108–1112.
SACSAC-2002-DingDP #data type #using
Decision tree classification of spatial data streams using Peano Count Trees (QD, QD, WP), pp. 413–417.
SACSAC-2002-NevesBR #game studies #learning
Learning the risk board game with classifier systems (AN, OB, ACR), pp. 585–589.
TPDLECDL-2001-FuhrHMMS #evaluation #library
Digital Libraries: A Generic Classification and Evaluation Scheme (NF, PH, MM, AM, IS), pp. 187–199.
TPDLECDL-2001-MatthesNS #named
C-Merge: A Tool for Policy-Based Merging of Resource Classifications (FM, CN, US), pp. 352–365.
TPDLECDL-2001-SemeraroFFE #documentation #modelling
Document Classification and Interpretation through the Inference of Logic-Based Models (GS, SF, NF, FE), pp. 59–70.
ICDARICDAR-2001-AkselaLOK #adaptation
Rejection Methods for an Adaptive Committee Classifier (MA, JL, EO, JK), pp. 982–986.
ICDARICDAR-2001-BagdanovW #documentation #fine-grained #first-order #graph #random #using
Fine-Grained Document Genre Classification Using First Order Random Graphs (ADB, MW), pp. 79–85.
ICDARICDAR-2001-BarakatB #geometry
Training with Positive and Negative Data Samples: Effects on a Classifier for Hand-Drawn Geometric Shapes (HB, DB), pp. 1017–1021.
ICDARICDAR-2001-CesariniLMS #documentation #encoding
Encoding of Modified X-Y Trees for Document Classification (FC, ML, SM, GS), pp. 1131–1136.
ICDARICDAR-2001-ChaS #algorithm #analysis
Apriori Algorithm for Sub-category Classification Analysis of Handwriting (SHC, SNS), pp. 1022–1025.
ICDARICDAR-2001-DaWM #analysis #fuzzy
Character Preclassification Based on Fuzzy Typographical Analysis (LD, PW, BM), pp. 74–78.
ICDARICDAR-2001-DiligentiGMS #documentation #html #modelling
Classification of HTML Documents by Hidden Tree-Markov Models (MD, MG, MM, FS), pp. 849–853.
ICDARICDAR-2001-HoN #constraints
Exploration of Contextual Constraints for Character Pre-Classification (TKH, GN), pp. 450–454.
ICDARICDAR-2001-HoqueF #learning
An Improved Learning Scheme for the Moving Window Classifier (SH, MCF), pp. 607–611.
ICDARICDAR-2001-KangL #multi
Experimental Results on the Construction of Multiple Classifiers Recognizing Handwritten Numerals (HJK, SWL), pp. 1026–1030.
ICDARICDAR-2001-NatteeN #comprehension #documentation #geometry #machine learning #online #using
Geometric Method for Document Understanding and Classification Using On-line Machine Learning (CN, MN), pp. 602–606.
ICDARICDAR-2001-Ratzlaff #online #recognition
A Scanning n-tuple Classifier for Online Recognition of Handwritten Digits (EHR), pp. 18–22.
ICDARICDAR-2001-SerraduraSV #markov #modelling #using #web
Web Sites Thematic Classification Using Hidden Markov Models (LS, MS, NV), pp. 1094–1099.
ICDARICDAR-2001-SirlantzisF #configuration management #multi #novel #recognition #self
Investigation of a Novel Self-configurable Multiple Classifier System for Character Recognition (KS, MCF), pp. 1002–1006.
ICDARICDAR-2001-TeredesaiG #approach #optimisation
Active Digit Classifiers: A Separability Optimization Approach to Emulate Cognition (AT, VG), pp. 401–405.
ICDARICDAR-2001-WangHP01a #evaluation #performance
Zone Content Classification and its Performance Evaluation (YW, RMH, ITP), pp. 540–544.
ICDARICDAR-2001-WengH #image #incremental #online
Incremental Hierarchical Discriminant Regression for Online Image Classification (JW, WSH), pp. 476–480.
ICDARICDAR-2001-YeCS #reduction #using
Reduction of the Classification Cost Using Hierarchical Classifiers based on the k-NN Rule (XY, MC, CYS), pp. 716–720.
JCDLJCDL-2001-LiuW #automation #feature model
Feature selection for automatic classification of musical instrument sounds (ML, CW), pp. 247–248.
JCDLJCDL-2001-PanFV #mining #named #video
VideoGraph: a new tool for video mining and classification (JYP, CF), pp. 116–117.
ICSMEICSM-2001-BassinS #fault #legacy #maintenance #orthogonal #outsourcing
Managing the Maintenance of Ported, Outsourced, and Legacy Software via Orthogonal Defect Classification (KB, PS), p. 726–?.
ICEISICEIS-v1-2001-RobardetV #case study
A Preliminary Study of a New Classification to Build Homogeneous Patient’s Groups in Home-Based Care (CR, CV), pp. 397–403.
CIKMCIKM-2001-Al-KofahiTVTJ #categorisation #multi
Combining Multiple Classifiers for Text Categorization (KAK, AT, AV, TT, PJ), pp. 97–104.
CIKMCIKM-2001-GohCC #image
SVM Binary Classifier Ensembles for Image Classification (KG, EYC, KTC), pp. 395–402.
CIKMCIKM-2001-NottelmannF #datalog #learning #probability
Learning Probabilistic Datalog Rules for Information Classification and Transformation (HN, NF), pp. 387–394.
CIKMCIKM-2001-SattlerD #database #sql
SQL Database Primitives for Decision Tree Classifiers (KUS, OD), pp. 379–386.
CIKMCIKM-2001-ToutanovaCPH #set
Text Classification in a Hierarchical Mixture Model for Small Training Sets (KT, FC, KP, TH), pp. 105–112.
CIKMCIKM-2001-ZelikovitzH #using
Using LSI for Text Classification in the Presence of Background Text (SZ, HH), pp. 113–118.
ICMLICML-2001-DobraG #bias
Bias Correction in Classification Tree Construction (AD, JG), pp. 90–97.
ICMLICML-2001-DomeniconiG #approach #approximate #dataset #multi #nearest neighbour #performance #query #scalability
An Efficient Approach for Approximating Multi-dimensional Range Queries and Nearest Neighbor Classification in Large Datasets (CD, DG), pp. 98–105.
ICMLICML-2001-GartnerF #named
WBCsvm: Weighted Bayesian Classification based on Support Vector Machines (TG, PAF), pp. 154–161.
ICMLICML-2001-LangfordSM #bound #predict
An Improved Predictive Accuracy Bound for Averaging Classifiers (JL, MWS, NM), pp. 290–297.
ICMLICML-2001-LatinneSD #multi #problem
Adjusting the Outputs of a Classifier to New a Priori Probabilities May Significantly Improve Classification Accuracy: Evidence from a multi-class problem in remote sensing (PL, MS, CD), pp. 298–305.
ICMLICML-2001-NgJ #convergence #feature model
Convergence rates of the Voting Gibbs classifier, with application to Bayesian feature selection (AYN, MIJ), pp. 377–384.
ICMLICML-2001-RozsypalK #algorithm #nearest neighbour #search-based #using
Using the Genetic Algorithm to Reduce the Size of a Nearest-Neighbor Classifier and to Select Relevant Attributes (AR, MK), pp. 449–456.
ICMLICML-2001-SebbanNL
Boosting Neighborhood-Based Classifiers (MS, RN, SL), pp. 505–512.
ICMLICML-2001-ShakhnarovichEB #evaluation #statistics
Smoothed Bootstrap and Statistical Data Cloning for Classifier Evaluation (GS, REY, YB), pp. 521–528.
ICMLICML-2001-ZadroznyE #naive bayes #probability
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers (BZ, CE), pp. 609–616.
KDDKDD-2001-BujaL #data mining #mining
Data mining criteria for tree-based regression and classification (AB, YSL), pp. 27–36.
KDDKDD-2001-CarageaCH #using
Gaining insights into support vector machine pattern classifiers using projection-based tour methods (DC, DC, VH), pp. 251–256.
KDDKDD-2001-FungM
Proximal support vector machine classifiers (GF, OLM), pp. 77–86.
KDDKDD-2001-IndurkhyaW #problem #rule-based
Solving regression problems with rule-based ensemble classifiers (NI, SMW), pp. 287–292.
KDDKDD-2001-MoodySV #automation
Data filtering for automatic classification of rocks from reflectance spectra (JM, RBdAeS, JV), pp. 347–352.
KDDKDD-2001-StreetK #algorithm #scalability #streaming
A streaming ensemble algorithm (SEA) for large-scale classification (WNS, YK), pp. 377–382.
MLDMMLDM-2001-Krzyzak #learning #network #using
Nonlinear Function Learning and Classification Using Optimal Radial Basis Function Networks (AK), pp. 217–225.
MLDMMLDM-2001-MottlDSKM #pattern matching #pattern recognition #recognition
Featureless Pattern Recognition in an Imaginary Hilbert Space and Its Application to Protein Fold Classification (VM, SD, OS, CAK, IBM), pp. 322–336.
MLDMMLDM-2001-Perner #question #reasoning
Are Case-Based Reasoning and Dissimilarity-Based Classification Two Sides of the Same Coin? (PP), pp. 35–51.
MLDMMLDM-2001-PhamWS #detection #network
Face Detection by Aggregated Bayesian Network Classifiers (TVP, MW, AWMS), pp. 249–262.
SEKESEKE-2001-MorenoS #detection #requirements
A Method for Detection, Classification and Resolution of Discrepancies in Viewpoint-based Requirements Engineering (AMM, AS), pp. 110–119.
SIGIRSIGIR-2001-ArampatzisH #adaptation #optimisation
The Score-Distributional Threshold Optimization for Adaptive Binary Classification Tasks (AA, AvH), pp. 285–293.
SIGIRSIGIR-2001-DrewL #using
Construction of a Hierarchical Classifier Schema Using a Combination of Text-Based and Image-Based Approaches (MSD, CL), pp. 438–439.
SIGIRSIGIR-2001-Joachims #learning #statistics
A Statistical Learning Model of Text Classification for Support Vector Machines (TJ), pp. 128–136.
SIGIRSIGIR-2001-OakesGF #documentation
A Method Based on the Chi-Square Test for Document Classification (MPO, RJG, HF), pp. 440–441.
SIGIRSIGIR-2001-StokesC #detection #documentation #semantics
Combining Semantic and Syntactic Document Classifiers to Improve First Story Detection (NS, JC), pp. 424–425.
ECOOPECOOP-2001-DrossopoulouDDG
Fickle : Dynamic Object Re-classification (SD, FD, MDC, PG), pp. 130–149.
DATEDATE-2001-OlbrichRB #algorithm #analysis
An improved hierarchical classification algorithm for structural analysis of integrated circuits (MO, AR, EB), p. 807.
CBSECBSE-2000-ThomasonBL #architecture #component
CLARiFi An Architecture for Component Classification and Brokerage (ST, PB, SL), p. 17.
TPDLECDL-2000-Pasquier #automation #database #functional #library #order #topic
Functional and Intentional Limitations of Interactivity on Content Indexing Topics: Possible Uses of Automatic Classification and Contents Extraction Systems, in Order to Create Digital Libraries Databases (FP), pp. 219–228.
VLDBVLDB-2000-LuL #scalability
Decision Tables: Scalable Classification Exploring RDBMS Capabilities (HL, HL), pp. 373–384.
IWPCIWPC-2000-GirardW #approach #data type #detection
Evaluating the Accessor Classification Approach to Detect Abstract Data Types (JFG, MW), pp. 87–95.
ICEISICEIS-2000-Sato-Ilic #fuzzy #relational
Classification Based on Relational Fuzzy C-Means for 3-Way Data (MSI), pp. 217–221.
CIKMCIKM-2000-MeretakisFLL #scalability
Scalable association-based text classification (DM, DF, HL, SL), pp. 5–11.
ICMLICML-2000-AllweinSS #approach #multi
Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers (ELA, RES, YS), pp. 9–16.
ICMLICML-2000-BennettB #geometry
Duality and Geometry in SVM Classifiers (KPB, EJB), pp. 57–64.
ICMLICML-2000-BowersGL
Classification of Individuals with Complex Structure (AFB, CGGC, JWL), pp. 81–88.
ICMLICML-2000-BrutlagM #challenge #email
Challenges of the Email Domain for Text Classification (JDB, CM), pp. 103–110.
ICMLICML-2000-CampbellCS #learning #query #scalability
Query Learning with Large Margin Classifiers (CC, NC, AJS), pp. 111–118.
ICMLICML-2000-Domingos #problem
Bayesian Averaging of Classifiers and the Overfitting Problem (PMD), pp. 223–230.
ICMLICML-2000-Ghani #using
Using Error-Correcting Codes for Text Classification (RG), pp. 303–310.
ICMLICML-2000-HsuHW #naive bayes #why
Why Discretization Works for Naive Bayesian Classifiers (CNH, HJH, TTW), pp. 399–406.
ICMLICML-2000-JuKS #gesture
State-based Classification of Finger Gestures from Electromyographic Signals (PJ, LPK, YS), pp. 439–446.
ICMLICML-2000-KaynakA #multi
MultiStage Cascading of Multiple Classifiers: One Man’s Noise is Another Man’s Data (CK, EA), pp. 455–462.
ICMLICML-2000-KubatC #nearest neighbour #subclass
Voting Nearest-Neighbor Subclassifiers (MK, MCJ), pp. 503–510.
ICMLICML-2000-MargineantuD #evaluation
Bootstrap Methods for the Cost-Sensitive Evaluation of Classifiers (DDM, TGD), pp. 583–590.
ICMLICML-2000-MullinS #nearest neighbour
Complete Cross-Validation for Nearest Neighbor Classifiers (MDM, RS), pp. 639–646.
ICMLICML-2000-TongK #learning
Support Vector Machine Active Learning with Application sto Text Classification (ST, DK), pp. 999–1006.
ICMLICML-2000-VilaltaO #bias #distance #evaluation #metric #quantifier
A Quantification of Distance Bias Between Evaluation Metrics In Classification (RV, DO), pp. 1087–1094.
ICMLICML-2000-WesterdijkW #modelling #multi #using
Classification with Multiple Latent Variable Models using Maximum Entropy Discrimination (MW, WW), pp. 1143–1150.
ICMLICML-2000-WilliamsS #kernel
The Effect of the Input Density Distribution on Kernel-based Classifiers (CKIW, MWS), pp. 1159–1166.
ICMLICML-2000-ZelikovitzH #problem #using
Improving Short-Text Classification using Unlabeled Data for Classification Problems (SZ, HH), pp. 1191–1198.
ICPRICPR-v1-2000-ClavierTLDL #sorting
Classifiers Combination for Forms Sorting (EC, ÉT, ML, SD, JL), pp. 1932–1935.
ICPRICPR-v1-2000-GongL #segmentation #video
Video Shot Segmentation and Classification (YG, XL), pp. 1860–1863.
ICPRICPR-v1-2000-HeidemannLR #network #visual notation
A System for Various Visual Classification Tasks Based on Neural Networks (GH, DL, HJR), pp. 1009–1012.
ICPRICPR-v1-2000-PaquisLK #using
Road Surface Classification by Thresholding Using Morphological Pyramid (SP, VL, HK), pp. 1334–1337.
ICPRICPR-v1-2000-PrabhakarJWPB #verification
Minutia Verification and Classification for Fingerprint Matching (SP, AKJ, JW, SP, RMB), pp. 1025–1029.
ICPRICPR-v1-2000-SinghMH #image #segmentation
FLIR Image Segmentation and Natural Object Classification (SS, MM, JFH), pp. 1681–1684.
ICPRICPR-v1-2000-YangM #gender #visual notation
Support Vector Machines for Visual Gender Classification (MHY, BM), pp. 5115–5118.
ICPRICPR-v2-2000-Abe #fuzzy
Generalization Improvement of a Fuzzy Classifier with Pyramidal Membership Functions (SA), pp. 2211–2214.
ICPRICPR-v2-2000-AlexandreCK #independence #using
Combining Independent and Unbiased Classifiers Using Weighted Average (LAA, ACC, MSK), pp. 2495–2498.
ICPRICPR-v2-2000-BaggenstossN #probability #using
A Theoretically Optimal Probabilistic Classifier Using Class-Specific Features (PMB, HN), pp. 2763–2768.
ICPRICPR-v2-2000-BeiraghiAAS #fault #fuzzy #recognition
Application of Fuzzy Integrals in Fusion of Classifiers for Low Error Rate Handwritten Numerals Recognition (SB, MA, MASA, MS), pp. 2487–2490.
ICPRICPR-v2-2000-ChazalR #comparison #using
A Comparison of the Use of Different Wavelet Coefficients for the Classification of the Electrocardiogram (PdC, RBR), pp. 2255–2258.
ICPRICPR-v2-2000-ChoKBBY #image
Core-Based Fingerprint Image Classification (BHC, JSK, JHB, IGB, KYY), pp. 2859–2862.
ICPRICPR-v2-2000-ChouS #algorithm #learning #multi
A Hierarchical Multiple Classifier Learning Algorithm (YYC, LGS), pp. 2152–2155.
ICPRICPR-v2-2000-Duin
Classifiers in Almost Empty Spaces (RPWD), pp. 2001–2007.
ICPRICPR-v2-2000-GaoD #algorithm #feature model #on the
On Improvement of Feature Extraction Algorithms for Discriminative Pattern Classification (JG, XD), pp. 2101–2104.
ICPRICPR-v2-2000-GiacintoR #framework
A Theoretical Framework for Dynamic Classifier Selection (GG, FR), pp. 2008–2011.
ICPRICPR-v2-2000-GiacintoRF #clustering #design #effectiveness #multi
Design of Effective Multiple Classifier Systems by Clustering of Classifiers (GG, FR, GF), pp. 2160–2163.
ICPRICPR-v2-2000-GoodeG #parametricity
Semi-Parametric Signal Classification (AJG, RHG), pp. 2622–2625.
ICPRICPR-v2-2000-HamadaSHT #automation #image
Automated Construction of Image Processing Procedure Based on Misclassification Condition (TH, AS, JiH, JiT), pp. 2430–2433.
ICPRICPR-v2-2000-HoB #complexity #problem
Measuring the Complexity of Classification Problems (TKH, MB), pp. 2043–2047.
ICPRICPR-v2-2000-HuangCSG #nearest neighbour #prototype
Constructing Optimized Prototypes for Nearest Neighbor Classifiers (YSH, CCC, JWS, WELG), pp. 2017–2020.
ICPRICPR-v2-2000-JuanV #edit distance #normalisation #on the #performance #string #using
On the Use of Normalized Edit Distances and an Efficient k-NN Search Technique (k-AESA) for Fast and Accurate String Classification (AJ, EV), pp. 2676–2679.
ICPRICPR-v2-2000-Kangas #comparison #nearest neighbour #prototype #representation
Comparison between Two Prototype Representation Schemes for a Nearest Neighbor Classifier (JK), pp. 2773–2776.
ICPRICPR-v2-2000-KangL #multi
An Information-Theoretic Strategy for Constructing Multiple Classifier Systems (HJK, SWL), pp. 2483–2486.
ICPRICPR-v2-2000-KeglKN #complexity #learning #network
Radial Basis Function Networks and Complexity Regularization in Function Learning and Classification (BK, AK, HN), pp. 2081–2086.
ICPRICPR-v2-2000-KimKNS #recognition #word
A Methodology of Combining HMM and MLP Classifiers for Cursive Word Recognition (JHK, KKK, CPN, CYS), pp. 2319–2322.
ICPRICPR-v2-2000-KudoIS
A Histogram-Based Classifier on Overlapped Bins (MK, HI, MS), pp. 2029–2033.
ICPRICPR-v2-2000-KunchevaWSD #independence #question
Is Independence Good For Combining Classifiers? (LIK, CJW, CAS, RPWD), pp. 2168–2171.
ICPRICPR-v2-2000-MalekTA #fault
Effect of the Feature Vector Size on the Generalization Error: The Case of MLPNN and RBFNN Classifiers (JEM, RT, AMA), pp. 2630–2633.
ICPRICPR-v2-2000-Martinez-HinarejosJC #string #using
Use of Median String for Classification (CDMH, AJ, FC), pp. 2903–2906.
ICPRICPR-v2-2000-MascarillaF
Another Look at Combining Rejection-Based Pattern Classifiers (LM, CF), pp. 2156–2159.
ICPRICPR-v2-2000-MatsakisW
Orbit and Sinus Classification Based on Force Histogram Computation (PM, LW), pp. 2451–2454.
ICPRICPR-v2-2000-MetzlerAPL #image #matrix #multi
Texture Classification of Graylevel Images by Multiscale Cross-Cooccurrence Matrices (VM, TA, CP, TML), pp. 2549–2552.
ICPRICPR-v2-2000-MitaniH #design #nearest neighbour #using
Classifier Design Based on the Use of Nearest Neighbor Samples (YM, YH), pp. 2769–2772.
ICPRICPR-v2-2000-MiyamotoHM #design #polynomial #using
Use of Bootstrap Samples in Quadratic Classifier Design (TM, YH, YM), pp. 2789–2792.
ICPRICPR-v2-2000-MollinedaFV #clustering #prototype
A Cluster-Based Merging Strategy for Nearest Prototype Classifiers (RAM, FJF, EV), pp. 2755–2758.
ICPRICPR-v2-2000-MutoNH #evaluation
Evaluation of a Modified Parzen Classifier in High Dimensional Spaces (YM, HN, YH), pp. 2067–2070.
ICPRICPR-v2-2000-NgB #segmentation #using
Supervised Texture Segmentation using DWT and a Modified K-NN Classifier (BWN, AB), pp. 2545–2548.
ICPRICPR-v2-2000-PekalskaD #pattern matching #pattern recognition #recognition
Classifiers for Dissimilarity-Based Pattern Recognition (EP, RPWD), pp. 2012–2016.
ICPRICPR-v2-2000-PerantonisPV #analysis #component #paradigm #using
Supervised Principal Component Analysis Using a Smooth Classifier Paradigm (SJP, SP, VV), pp. 2109–2112.
ICPRICPR-v2-2000-Raudys #adaptation
Prior Weights in Adaptive Pattern Classification (SR), pp. 6010–6013.
ICPRICPR-v2-2000-RibaCVJ #invariant
Methods for Invariant Signature Classification (JRR, AC, SV, IJ), pp. 2953–2956.
ICPRICPR-v2-2000-SarkarN
Classification of Style-Constrained Pattern-Fields (PS, GN), pp. 2855–2858.
ICPRICPR-v2-2000-Sato #fault #learning
A Learning Method for Definite Canonicalization Based on Minimum Classification Error (AS), pp. 2199–2202.
ICPRICPR-v2-2000-Singh #locality
EEG Data Classification with Localized Structural Information (SS), pp. 2271–2274.
ICPRICPR-v2-2000-Tambouratzis
Improving the Classification Accuracy of the Scanning n-tuple Method (GT), pp. 6046–6049.
ICPRICPR-v2-2000-TangXM00a
Two-Step Classification Based on Scale Space (MT, JX, SM), pp. 2899–2902.
ICPRICPR-v2-2000-VailayaJ
Reject Option for VQ-Based Bayesian Classification (AV, AKJ), pp. 2048–2051.
ICPRICPR-v2-2000-VuoriLOK #adaptation #online #prototype
Controlling On-Line Adaptation of a Prototype-Based Classifier for Handwritten Characters (VV, JL, EO, JK), pp. 2331–2334.
ICPRICPR-v2-2000-WohlerKA #image #recognition #sequence
Pedestrian Recognition by Classification of Image Sequences — Global Approaches vs. Local Spatio-Temporal Processing (CW, UK, JKA), pp. 2540–2544.
ICPRICPR-v2-2000-WuZZ #network #recognition
A Neural Network Based Classifier for Handwritten Chinese Character Recognition (MW, BZ, LZ), pp. 2561–2564.
ICPRICPR-v2-2000-XiaoWD #adaptation #recognition
Adaptive Combination of Classifiers and its Application to Handwritten Chinese Character Recognition (BX, CHW, RD), pp. 2327–2330.
ICPRICPR-v2-2000-YuJB #recognition #visual notation
Combining Acoustic and Visual Classifiers for the Recognition of Spoken Sentences (KY, XJ, HB), pp. 2491–2494.
ICPRICPR-v2-2000-ZhangDL #design #feature model #multi #recognition
Multi-Scale Feature Extraction and Nested-Subset Classifier Design for High Accuracy Handwritten Character Recognition (JZ, XD, CL), pp. 2581–2584.
ICPRICPR-v3-2000-ChantlerM #invariant #on the #using
On the Use of Gradient Space Eigenvalues for Rotation Invariant Texture Classification (MJC, GM), pp. 3943–3946.
ICPRICPR-v3-2000-ChetverikovF #invariant
Affine-Invariant Texture Classification (DC, ZF), pp. 3901–3904.
ICPRICPR-v3-2000-GaoQL #fuzzy
Fuzzy Classification of Generic Edge Features (QG, DQ, SL), pp. 3672–3675.
ICPRICPR-v3-2000-HuangCH #adaptation
An Adaptive Model for Texture Classification (YH, KLC, ZH), pp. 3905–3908.
ICPRICPR-v3-2000-HufnaglU #fault #performance
Resolving a Defect in Quadrant-Based Classification for Fast Block-Matching (CH, AU), pp. 3203–3206.
ICPRICPR-v3-2000-Kiema #automation #data fusion #using
Wavelet Compression and Data Fusion: An Investigation into the Automatic Classification of Urban Environments using Color Photography and Laser Scanning Data (JBKK), pp. 3089–3093.
ICPRICPR-v3-2000-MaenpaaOPM #robust #set
Robust Texture Classification by Subsets of Local Binary Patterns (TM, TO, MP, MS), pp. 3947–3950.
ICPRICPR-v3-2000-MaenpaaPO #multi
Texture Classification by Multi-Predicate Local Binary Pattern Operators (TM, MP, TO), pp. 3951–3954.
ICPRICPR-v3-2000-MostafaPF
A Two-Step Fuzzy-Bayesian Classification for High Dimensional Data (MGHM, TCP, AAF), pp. 3421–3424.
ICPRICPR-v3-2000-Ney #modelling #probability #recognition #speech
Stochastic Modeling: From Pattern Classification to Speech Recognition and Translation (HN), pp. 3025–3032.
ICPRICPR-v3-2000-NgR #gesture #recognition
Gesture Recognition via Pose Classification (CWN, SR), pp. 3703–3708.
ICPRICPR-v3-2000-SebeL00a
Wavelet Based Texture Classification (NS, MSL), pp. 3959–3962.
ICPRICPR-v3-2000-VandenbrouckeMP #image #segmentation
Color Image Segmentation by Supervised Pixel Classification in a Color Texture Feature Space: Application to Soccer Image Segmentation (NV, LM, JGP), pp. 3625–3628.
ICPRICPR-v3-2000-VertanB #normalisation #representation
Color Texture Classification by Normalized Color Space Representation (CV, NB), pp. 3584–3587.
ICPRICPR-v3-2000-VriesV #3d #adaptation #detection #estimation #image
Scale-Adaptive Landmark Detection, Classification and Size Estimation in 3D Object-Background Images (RGdV, PWV), pp. 7026–7029.
ICPRICPR-v4-2000-IwamotoTC #named #realtime
REFLICS: Real-Time Flow Imaging and Classification System (SI, MMT, DMCJ), pp. 4689–4692.
ICPRICPR-v4-2000-KampelS
Color Classification of Archaeological Fragments (MK, RS), pp. 4771–4774.
ICPRICPR-v4-2000-SanchezM #3d
Fusing 3D Information for Crop/Weeds Classification (AJS, JAM), pp. 4295–4298.
KDDKDD-2000-AnkerstEK #effectiveness #towards
Towards an effective cooperation of the user and the computer for classification (MA, ME, HPK), pp. 179–188.
KDDKDD-2000-FungM
Data selection for support vector machine classifiers (GF, OLM), pp. 64–70.
KDDKDD-2000-InselbergA #visualisation
Classification and visualization for high-dimensional data (AI, TA), pp. 370–374.
KDDKDD-2000-WangMSW #biology #case study #data mining #mining #network #sequence
Application of neural networks to biological data mining: a case study in protein sequence classification (JTLW, QM, DS, CHW), pp. 305–309.
KDDKDD-2000-YiS #documentation
A classifier for semi-structured documents (JY, NS), pp. 340–344.
SIGIRSIGIR-2000-DumaisC #web
Hierarchical classification of Web content (STD, HC), pp. 256–263.
SIGIRSIGIR-2000-KimHZ #naive bayes
Text filtering by boosting naive bayes classifiers (YHK, SYH, BTZ), pp. 168–175.
SIGIRSIGIR-2000-ManevitzY #documentation #network #using
Document classification on neural networks using only positive examples (LMM, MY), pp. 304–306.
SIGIRSIGIR-2000-TakasuA #categorisation #comparison
Variance based classifier comparison in text categorization (AT, KA), pp. 316–317.
FSEFSE-2000-NaumovichC
Classifying properties: an alternative to the safety-liveness classification (GN, LAC), pp. 159–168.
SACSAC-2000-ByunL #using
Form Classification Using DP Matching (YB, YL), pp. 1–4.
SACSAC-2000-KloseKST #fault #symmetry
Controlling Asymmetric Errors in Neuro-Fuzzy Classification (AK, RK, KS, UT), pp. 505–509.
HPCAHPCA-2000-HaungsSF #analysis #branch #metric
Branch Transition Rate: A New Metric for Improved Branch Classification Analysis (MH, PS, MKF), pp. 241–250.
STOCSTOC-2000-GuptaT #algorithm #approximate #constant #problem
A constant factor approximation algorithm for a class of classification problems (AG, ÉT), pp. 652–658.
ISSTAISSTA-2000-KolanoK #analysis #realtime
Classification schemes to aid in the analysis of real-time systems (PZK, RAK), pp. 86–95.
DL-1999-AbbadeniZW #image #retrieval #web
Image Classification and Retrieval on the World Wide Web (NA, DZ, SW), pp. 208–209.
DL-1999-ArdoK #automation
Creation and Automatic Classification of a Robot-Generated Subject Index (AA, TK), pp. 210–211.
DL-1999-Larkey
A Patent Search and Classification System (LSL), pp. 179–187.
DL-1999-Lim #image #keyword #visual notation
Learnable Visual Keywords for Image Classification (JHL), pp. 139–145.
ICDARICDAR-1999-AtukoraleS
Combining Classifiers based on Confidence Values (ASA, PNS), pp. 37–40.
ICDARICDAR-1999-ClavierCL #approach #image #sorting
Image Sorting — Image Classification: A Global Approach (EC, SC, JL), pp. 123–126.
ICDARICDAR-1999-DehkordiSW #approach #component #word
A Principal Component Approach to Classification of Handwritten Words (MED, NS, RJW), pp. 781–784.
ICDARICDAR-1999-Hobby #composition #geometry #layout
Page Decomposition and Signature Finding via Shape Classification and Geometric Layout (JDH), pp. 555–558.
ICDARICDAR-1999-HuKW #comparison #documentation #image #layout
Document Image Layout Comparison and Classification (JH, RSK, GTW), pp. 285–288.
ICDARICDAR-1999-JungSS #multi #using
Multifont Classification using Typographical Attributes (MCJ, YCS, SNS), pp. 353–356.
ICDARICDAR-1999-KangL #fault
Combining Classifiers based on Minimization of a Bayes Error Rate (HJK, SWL), pp. 398–401.
ICDARICDAR-1999-Kawatani #recognition #using
Handwritten Kanji Recognition using Combined Complementary Classifiers in a Cascade Arrangement (TK), pp. 503–506.
ICDARICDAR-1999-LeeG #automation
Automatic Classification of Deformed Handwritten Numeral Characters (LLL, NRG), pp. 269–272.
ICDARICDAR-1999-LiN #documentation #learning
A Document Classification and Extraction System with Learning Ability (XL, PAN), pp. 197–200.
ICDARICDAR-1999-LiuN99a #algorithm #learning #nearest neighbour #prototype #recognition
Prototype Learning Algorithms for Nearest Neighbor Classifier with Application to Handwritten Character Recognition (CLL, MN), pp. 378–381.
ICDARICDAR-1999-RibertLE #design #distributed #performance #recognition
Designing Efficient Distributed Neural Classifiers: Application to Handwritten Digit Recognition (AR, YL, AE), pp. 265–268.
ICDARICDAR-1999-StockerRL #network #problem #self
Self-organized Classification Problem Solving with Yprel Neural Networks (ES, AR, YL), pp. 390–393.
ICDARICDAR-1999-WuS #distance #multi #network #recognition #using
Unconstrained Handwritten Numeral Recognition using Hausdorff Distance and Multi-Layer Neural Network Classifier (XW, PS), pp. 249–252.
VLDBVLDB-1999-WangZL #proximity #using
Building Hierarchical Classifiers Using Class Proximity (KW, SZ, SCL), pp. 363–374.
ICSMEICSM-1999-MendoncaK #component #comprehension #distributed
Component Module Classification for Distributed Software Understanding (NCM, JK), p. 119–?.
HCIHCI-CCAD-1999-NisslerMH #3d #design #how
How to get the right outfit for my agent? Classification — and design methodology for a virtual shopping assistant in a 3D world (JN, JM, AH), pp. 162–166.
HCIHCI-EI-1999-HartsonAWR #framework #problem #usability
The User Action Framework: A Theory-Based Foundation for Inspection and Classification of Usability Problems (HRH, TSA, RCW, LvR), pp. 1058–1062.
HCIHCI-EI-1999-KandaN #visual notation
Studies on Classification of Similar Trademarks Corresponding to Human Visual Cognitive Sense (TK, HN), pp. 501–505.
CAiSECAiSE-1999-BeckerM #framework #towards #workflow
Towards a Classification Framework for Application Granularity in Workflow Management Systems (JB, MzM), pp. 411–416.
CIKMCIKM-1999-DolinPBA #automation #evaluation #information retrieval
Practical evaluation of IR within automated classification systems (RD, JP, MB, RA), pp. 322–329.
CIKMCIKM-1999-GeffnerAAS #library #scalability #using
Browsing Large Digital Library Collections Using Classification Hierarchies (SG, DA, AEA, TRS), pp. 195–201.
CIKMCIKM-1999-HsuL #algorithm
Classification Algorithms for NETNEWS Articles (WLH, SDL), pp. 114–121.
CIKMCIKM-1999-LiY #probability #using
Text Classification Using ESC-based Stochastic Decision Lists (HL, KY), pp. 122–130.
CIKMCIKM-1999-MatsudaF #documentation #retrieval #web
Task-Oriented World Wide Web Retrieval by Document Type Classification (KM, TF), pp. 109–113.
ICMLICML-1999-BlanzieriR #metric #nearest neighbour
A Minimum Risk Metric for Nearest Neighbor Classification (EB, FR), pp. 22–31.
ICMLICML-1999-CardieMP #parsing
Combining Error-Driven Pruning and Classification for Partial Parsing (CC, SM, DRP), pp. 87–96.
ICMLICML-1999-FanSZC #named
AdaCost: Misclassification Cost-Sensitive Boosting (WF, SJS, JZ, PKC), pp. 97–105.
ICMLICML-1999-Joachims #using
Transductive Inference for Text Classification using Support Vector Machines (TJ), pp. 200–209.
ICMLICML-1999-LangleyS #analysis #naive bayes
Tractable Average-Case Analysis of Naive Bayesian Classifiers (PL, SS), pp. 220–228.
ICMLICML-1999-ScottM #re-engineering
Feature Engineering for Text Classification (SS, SM), pp. 379–388.
KDDKDD-1999-AnkerstEEK #approach #interactive #visual notation
Visual Classification: An Interactive Approach to Decision Tree Construction (MA, CE, ME, HPK), pp. 392–396.
KDDKDD-1999-BonchiGMP #detection
A Classification-Based Methodology for Planning Audit Strategies in Fraud Detection (FB, FG, GM, DP), pp. 175–184.
KDDKDD-1999-Domingos #named
MetaCost: A General Method for Making Classifiers Cost-Sensitive (PMD), pp. 155–164.
KDDKDD-1999-KellyHA #performance
The Impact of Changing Populations on Classifier Performance (MGK, DJH, NMA), pp. 367–371.
KDDKDD-1999-LeshZO #mining #sequence
Mining Features for Sequence Classification (NL, MJZ, MO), pp. 342–346.
KDDKDD-1999-MeretakisW #naive bayes #using
Extending Naïve Bayes Classifiers Using Long Itemsets (DM, BW), pp. 165–174.
KDDKDD-T-1999-GehrkeLR
Classification and Regression: Money *can* Grow on Trees (JG, WYL, RR), pp. 1–73.
MLDMMLDM-1999-GiacintoR #automation #design #learning #multi
Automatic Design of Multiple Classifier Systems by Unsupervised Learning (GG, FR), pp. 131–143.
UMLUML-1999-BernerGJ #modelling #object-oriented
A Classification of Stereotypes for Object-Oriented Modeling Languages (SB, MG, SJ), pp. 249–264.
UMLUML-1999-MillerW #how #question
How Can Anything be Both a Classifier and a Package? (JM, RWB), pp. 584–597.
TOOLSTOOLS-EUROPE-1999-MensWD #architecture #using
Declaratively Codifying Software Architectures Using Virtual Software Classifications (KM, RW, TD), pp. 33–45.
ICSEICSE-1999-YakimovichBB #architecture #cost analysis #integration #off the shelf
Software Architecture Classification for Estimating the Cost of COTS Integration (DY, JMB, VRB), pp. 296–302.
DL-1998-HaasG
Page and Link Classifications: Connecting Diverse Resources (SWH, ESG), pp. 99–107.
TPDLECDL-1998-LiuDSCHDC #documentation #library #visualisation
Visualizing Document Classification: A Search Aid for the Digital Library (YHL, PD, MS, JTC, MTH, MD, JDC), pp. 555–567.
SIGMODSIGMOD-1998-ShintaniK #algorithm #mining #parallel
Parallel Mining Algorithms for Generalized Association Rules with Classification Hierarchy (TS, MK), pp. 25–36.
VLDBVLDB-1998-RastogiS #named
PUBLIC: A Decision Tree Classifier that Integrates Building and Pruning (RR, KS), pp. 404–415.
CSMRCSMR-1998-KawabeMUO #problem
Variable Classification Technique and Application to the Year 2000 Problem (KK, AM, SU, AO), pp. 44–51.
CIKMCIKM-1998-PapkaA #documentation #multi #using
Document Classification Using Multiword Features (RP, JA), pp. 124–131.
ICMLICML-1998-Bay #multi #nearest neighbour #set
Combining Nearest Neighbor Classifiers Through Multiple Feature Subsets (SDB), pp. 37–45.
ICMLICML-1998-BollackerG #architecture #reuse #scalability
A Supra-Classifier Architecture for Scalable Knowledge Reuse (KDB, JG), pp. 64–72.
ICMLICML-1998-CristianiniSS #scalability
Bayesian Classifiers Are Large Margin Hyperplanes in a Hilbert Space (NC, JST, PS), pp. 109–117.
ICMLICML-1998-FriedmanGL #network #parametricity
Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting (NF, MG, TJL), pp. 179–187.
ICMLICML-1998-MaronR #learning #multi
Multiple-Instance Learning for Natural Scene Classification (OM, ALR), pp. 341–349.
ICMLICML-1998-McCallumN #learning
Employing EM and Pool-Based Active Learning for Text Classification (AM, KN), pp. 350–358.
ICMLICML-1998-McCallumRMN
Improving Text Classification by Shrinkage in a Hierarchy of Classes (AM, RR, TMM, AYN), pp. 359–367.
ICMLICML-1998-PrecupU #approximate #using
Classification Using Phi-Machines and Constructive Function Approximation (DP, PEU), pp. 439–444.
ICPRICPR-1998-Aladjem #ml #network #recursion #reduction
Training of a ML neural network for classification via recursive reduction of the class separation (MA), pp. 450–452.
ICPRICPR-1998-ArikiS #multi #using
Classification of TV sports news by DCT features using multiple subspace method (YA, YS), pp. 1488–1491.
ICPRICPR-1998-BischofLP #robust
A robust subspace classifier (HB, AL, FP), pp. 114–116.
ICPRICPR-1998-BreukelenD #network
Neural network initialization by combined classifiers (MvB, RPWD), pp. 215–218.
ICPRICPR-1998-BulowS
Quaternionic gabor filters for local structure classification (TB, GS), pp. 808–810.
ICPRICPR-1998-FrelicotL
A pretopology-based supervised pattern classifier (CF, FL), pp. 106–109.
ICPRICPR-1998-GovindanDKP #analysis #component #independence
Independent component analysis applied to electrogram classification during atrial fibrillation (AG, GD, JK, JP), pp. 1662–1664.
ICPRICPR-1998-HerouxDRT #automation #identification
Classification method study for automatic form class identification (PH, SD, AR, ÉT), pp. 926–928.
ICPRICPR-1998-HojjatoleslamiK
Strategies for weighted combination of classifiers employing shared and distinct representations (AH, JK), pp. 338–340.
ICPRICPR-1998-HuetP #fuzzy #image #multi
A multi-scale fuzzy classification by knn. Application to the interpretation of aerial images (FH, SP), pp. 96–98.
ICPRICPR-1998-HuetP98a #fuzzy #image #multi #segmentation
Fusion of images after segmentation by various operators and interpretation by a multi-scale fuzzy classification (FH, SP), pp. 1843–1845.
ICPRICPR-1998-IivarinenV #adaptation #fault
An adaptive texture and shape based defect classification (JI, AV), pp. 117–122.
ICPRICPR-1998-KeeniNS #automation #estimation #generative #network #using
Automatic generation of initial weights and estimation of hidden units for pattern classification using neural networks (KK, KN, HS), pp. 1568–1571.
ICPRICPR-1998-KeglKN #learning #network #parametricity
Radial basis function networks in nonparametric classification and function learning (BK, AK, HN), pp. 565–570.
ICPRICPR-1998-Kraaijveld #comparison #parametricity
An experimental comparison of nonparametric classifiers for time-constrained classification tasks (MAK), pp. 428–435.
ICPRICPR-1998-Kwok #problem
Support vector mixture for classification and regression problems (JTYK), pp. 255–258.
ICPRICPR-1998-LamOX #learning
Application of Bayesian Ying-Yang criteria for selecting the number of hidden units with backpropagation learning to electrocardiogram classification (WKL, NO, LX), pp. 1686–1688.
ICPRICPR-1998-LashkiaA #performance
Test feature classifiers: performance and application (VL, SA), pp. 341–343.
ICPRICPR-1998-LiJ #documentation
Classification of text documents (YL, AKJ), pp. 1295–1297.
ICPRICPR-1998-Mizutani #fault #learning
Discriminative learning for minimum error and minimum reject classification (HM), pp. 136–140.
ICPRICPR-1998-NieuwoudtB #performance #using
Relative performance of correlation-based and feature-based classifiers of aircraft using radar range profiles (CN, ECB), pp. 1828–1832.
ICPRICPR-1998-PalauS #approximate #nearest neighbour #performance
The labelled cell classifier: a fast approximation to k nearest neighbors (AMP, RRS), pp. 823–827.
ICPRICPR-1998-Perner #analysis #image
Image analysis and classification of HEp-2 cells in fluorescent images (PP), pp. 1677–1679.
ICPRICPR-1998-PrevostM #automation #multi #recognition
Automatic allograph selection and multiple expert classification for totally unconstrained handwritten character recognition (LP, MM), pp. 381–383.
ICPRICPR-1998-QiTD #algorithm #feedback #search-based
Fingerprint classification system with feedback mechanism based on genetic algorithm (YQ, JT, RD), pp. 163–165.
ICPRICPR-1998-RodriguezMNZMP
A two-stage classifier for broken and blurred digits in forms (CR, JM, MN, AZ, JIM, JMP), pp. 1101–1105.
ICPRICPR-1998-SablatnigKZ #modelling #using
Hierarchical classification of paintings using face- and brush stroke models (RS, PK, EZ), pp. 172–174.
ICPRICPR-1998-SatoY #learning #using
A formulation of learning vector quantization using a new misclassification measure (AS, KY), pp. 322–325.
ICPRICPR-1998-ShahA #architecture #hybrid #performance #reasoning
A hybrid architecture for performance reasoning in classification systems (SS, JKA), pp. 326–330.
ICPRICPR-1998-SukanyaTS #image #multi #using
Image classification using the surface-shape operator and multiscale features (PS, RT, MS), pp. 334–337.
ICPRICPR-1998-SuriHS #automation #bound #polynomial
Automatic quadratic calibration for correction of pixel classification boundaries to an accuracy of 2.5 millimeters: an application in cardiac imaging (JSS, RMH, FHS), pp. 30–33.
ICPRICPR-1998-UchidaKMT #integration #statistics
Fingerprint card classification with statistical feature integration (KU, TK, MM, TT), pp. 1833–1839.
ICPRICPR-1998-WangLL #composition #markov #modelling #random #using
Texture classification using wavelet decomposition with Markov random field models (LW, JL, SZL), pp. 1613–1615.
ICPRICPR-1998-ZhangFY #composition #modelling #recognition
A modular classification scheme with elastic net models for handwritten digit recognition (BZ, MF, HY), pp. 1859–1861.
KDDKDD-1998-AlsabtiRS #dataset #named #scalability
CLOUDS: A Decision Tree Classifier for Large Datasets (KA, SR, VS), pp. 2–8.
KDDKDD-1998-CohenH #using
Joins that Generalize: Text Classification Using WHIRL (WWC, HH), pp. 169–173.
KDDKDD-1998-GraefeFC #database #on the #performance #scalability #sql #statistics
On the Efficient Gathering of Sufficient Statistics for Classification from Large SQL Databases (GG, UMF, SC), pp. 204–208.
KDDKDD-1998-KeoghP #clustering #feedback #performance #representation
An Enhanced Representation of Time Series Which Allows Fast and Accurate Classification, Clustering and Relevance Feedback (EJK, MJP), pp. 239–243.
KDDKDD-1998-KohaviS
Targeting Business Users with Decision Table Classifiers (RK, DS), pp. 249–253.
KDDKDD-1998-KontkanenMST #feature model #named
BAYDA: Software for Bayesian Classification and Feature Selection (PK, PM, TS, HT), pp. 254–258.
KDDKDD-1998-LiuHM #mining
Integrating Classification and Association Rule Mining (BL, WH, YM), pp. 80–86.
KDDKDD-1998-NakhaeizadehTL
Evaluating Usefulness for Dynamic Classification (GN, CT, CL), pp. 87–93.
KDDKDD-1998-RidgewayMRO #naive bayes
Interpretable Boosted Naïve Bayes Classification (GR, DM, TR, JO), pp. 101–104.
KDDKDD-1998-Rosset #comparison #evaluation #flexibility #named #performance #ranking
Ranking — Methods for Flexible Evaluation and Efficient Comparison of Classification Performance (SR), pp. 324–328.
KDDKDD-1998-Stolfo #database #mining
Mining Databases with Different Schemas: Integrating Incompatible Classifiers (ALP, SJS), pp. 314–318.
SIGIRSIGIR-1998-BakerM #clustering #word
Distributional Clustering of Words for Text Classification (LDB, AM), pp. 96–103.
SIGIRSIGIR-1998-LinSCHKH #approach #documentation #internet #mining #semantics
Extracting Classification Knowledge of Internet Documents with Mining Term Associations: A Semantic Approach (SHL, CSS, MCC, JMH, MTK, YMH), pp. 241–249.
SIGIRSIGIR-1998-RagasK #algorithm #corpus
Four Text Classification Algorithms Compared on a Dutch Corpus (HR, CHAK), pp. 369–370.
SACSAC-1998-HarandiR #distributed #problem
Classification and organizational issues in distributed problem solving (MTH, GR), pp. 65–69.
SACSAC-1998-Konstam #algorithm #programming #search-based #using
Group classification using a mix of genetic programming and genetic algorithms (AHK), pp. 308–312.
SACSAC-1998-LimaR
Maximum likelihood based classification for the microstructure of human sleep (JAL, ACR), pp. 60–64.
DACDAC-1998-XieB #finite #markov #performance
Efficient State Classification of Finite State Markov Chains (AX, PAB), pp. 605–610.
ICDARICDAR-1997-AlimogluA #multi
Combining Multiple Representations and Classifiers for Pen-based Handwritten Digit Recognitio (FA, EA), pp. 637–640.
ICDARICDAR-1997-AnisimovichRST #recognition #using
Using Combination of Structural, Feature and Raster Classifiers for Recognition of Handprinted Characters (KA, VR, AS, VT), pp. 881–885.
ICDARICDAR-1997-ArikiT #recognition
Indexing and Classification of TV News Articles Based on Telop Recognition (YA, TT), pp. 422–427.
ICDARICDAR-1997-BouletreauVSE #parametricity
Synthetic Parameters for Handwriting Classification (VB, NV, RS, HE), pp. 102–106.
ICDARICDAR-1997-DingLS #using
Classification of Oriental and European Scripts by Using Characteristic Features (JD, LL, CYS), pp. 1023–1027.
ICDARICDAR-1997-FrankeGKM #comparison #markov #modelling #polynomial #recognition
A Comparison of Gaussian Distribution and Polynomial Classifiers in a Hidden Markov Model Based System for the Recognition of Cursive Script (JF, JMG, AK, EM), pp. 515–518.
ICDARICDAR-1997-Horiuchi
Pattern Classification Method by Integrating Interval Feature Values (TH), pp. 847–850.
ICDARICDAR-1997-JunkerH #documentation #learning
Evaluating OCR and Non-OCR Text Representations for Learning Document Classifiers (MJ, RH), pp. 1060–1066.
ICDARICDAR-1997-KangK #framework #multi #probability
Probabilistic Framework for Combining Multiple Classifiers at Abstract Level (HJK, JHK), pp. 870–874.
ICDARICDAR-1997-KawataniS #component #design #difference #using
Complementary Classifier Design Using Difference Principal Components (TK, HS), pp. 875–880.
ICDARICDAR-1997-KimSC #approach #multi #recognition
A systematic approach to classifier selection on combining multiple classifiers for handwritten digit recognition (JK, KS, KC), pp. 459–462.
ICDARICDAR-1997-PrevostM #recognition
Static and Dynamic Classifier Fusion for Character Recognition (LP, MM), pp. 499–506.
ICDARICDAR-1997-TeoS #hybrid
A Hybrid Classifier for Recognizing Handwritten Numerals (RYMT, RS), pp. 283–287.
ICDARICDAR-1997-TsudaM #parametricity
A Nonparametric Density Model for Classification in a High Dimensional Space (KT, MM), pp. 1082–1087.
ICDARICDAR-1997-WaizumiKSN #learning #using
High speed rough classification for handwritten characters using hierarchical learning vector quantization (YW, NK, KS, YN), pp. 23–27.
ICALPICALP-1997-ManziniM #automaton #linear
A Complete and Efficiently Computable Topological Classification of D-dimensional Linear Cellular Automata over Zm (GM, LM), pp. 794–804.
ICMLICML-1997-AskerM #case study #detection #re-engineering
Feature Engineering and Classifier Selection: A Case Study in Venusian Volcano Detection (LA, RM), pp. 3–11.
ICMLICML-1997-Decatur #induction #learning
PAC Learning with Constant-Partition Classification Noise and Applications to Decision Tree Induction (SED), pp. 83–91.
ICMLICML-1997-VilaltaR #induction #multi
Integrating Feature Construction with Multiple Classifiers in Decision Tree Induction (RV, LAR), pp. 394–402.
KDDKDD-1997-AliMS #using
Partial Classification Using Association Rules (KA, SM, RS), pp. 115–118.
KDDKDD-1997-Bayardo #mining
Brute-Force Mining of High-Confidence Classification Rules (RJBJ), pp. 123–126.
KDDKDD-1997-Drucker #performance
Fast Committee Machines for Regression and Classification (HD), pp. 159–162.
KDDKDD-1997-LiuHC #using
Using General Impressions to Analyze Discovered Classification Rules (BL, WH, SC), pp. 31–36.
KDDKDD-1997-ProvostF #analysis #comparison #performance #visualisation
Analysis and Visualization of Classifier Performance: Comparison under Imprecise Class and Cost Distributions (FJP, TF), pp. 43–48.
STOCSTOC-1997-KhannaSW #constraints #problem
A Complete Classification of the Approximability of Maximization Problems Derived from Boolean Constraint Satisfaction (SK, MS, DPW), pp. 11–20.
CADECADE-1997-Nivelle #order
A Classification of Non-liftable Orders for Resolution (HdN), pp. 336–350.
VLDBVLDB-1996-ShaferAM #data mining #mining #named #parallel #scalability
SPRINT: A Scalable Parallel Classifier for Data Mining (JCS, RA, MM), pp. 544–555.
ICSMEICSM-1996-OwensWG #fault #using
Software Error Classification using Purify (HDO, BFW, MJG), pp. 104–113.
KDDAKDDM-1996-CheesemanS
Bayesian Classification (AutoClass): Theory and Results (PC, JS), pp. 153–180.
ICMLICML-1996-AkkusG #nearest neighbour
K Nearest Neighbor Classification on Feature Projections (AA, HAG), pp. 12–19.
ICMLICML-1996-DomingosP #independence
Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier (PMD, MJP), pp. 105–112.
ICMLICML-1996-GreinerGR #learning
Learning Active Classifiers (RG, AJG, DR), pp. 207–215.
ICMLICML-1996-OkamotoY #analysis #nearest neighbour
Theoretical Analysis of the Nearest Neighbor Classifier in Noisy Domains (SO, NY), pp. 355–363.
ICMLICML-1996-SinghP #learning #network #performance
Efficient Learning of Selective Bayesian Network Classifiers (MS, GMP), pp. 453–461.
ICPRICPR-1996-AchermannB #identification
Combination of face classifiers for person identification (BA, HB), pp. 416–420.
ICPRICPR-1996-BandyopadhyayMP
GA-based pattern classification: theoretical and experimental studies (SB, CAM, SKP), pp. 758–762.
ICPRICPR-1996-Bobrowski #learning #set
Piecewise-linear classifiers, formal neurons and separability of the learning sets (LB), pp. 224–228.
ICPRICPR-1996-BonifaziMNP #image #industrial #recognition
The classification of industrial sand-ores by image recognition methods (GB, PM, LN, GP), pp. 174–179.
ICPRICPR-1996-ChangL
Classification with nonexclusive patterns (IC, MHL), pp. 116–120.
ICPRICPR-1996-ChenLC #analysis #sequence #using
Handwritten Chinese character analysis and preclassification using stroke structural sequence (ZC, CWL, RHC), pp. 89–93.
ICPRICPR-1996-ChetverikovLKH #using
Zone classification using texture features (DC, JL, JK, RMH), pp. 676–680.
ICPRICPR-1996-CohenDE #image
Computerized classification of color textured perthite images (BC, ID, ME), pp. 601–605.
ICPRICPR-1996-CortijoB #automation #estimation #image #multi #parametricity
Automatic estimation of the LVQ-1 parameters. Applications to multispectral image classification (FJC, NPdlB), pp. 346–350.
ICPRICPR-1996-DiasBD #identification #using
Results of the use of Bayesian classifiers for identification of breast cancer cell nuclei (ÂVD, FB, MRD), pp. 508–512.
ICPRICPR-1996-DoeringW #composition #cost analysis #network #set
Feedforward neural networks for Bayes-optimal classification: investigations into the influence of the composition of the training set on the cost function (AD, HW), pp. 219–223.
ICPRICPR-1996-FerrariBG #array
A VLSI array processor accelerator for k-NN classification (AF, MB, RG), pp. 723–727.
ICPRICPR-1996-GonzalezC #functional #markov #random
The Markov random fields in functional neighbors as a texture model: applications in texture classification (AMG, DC), pp. 815–819.
ICPRICPR-1996-HepplewhiteS #pattern matching #pattern recognition #recognition #using
Texture classification using n-tuple pattern recognition (LH, TJS), pp. 159–163.
ICPRICPR-1996-HoekstraD #on the
On the nonlinearity of pattern classifiers (AH, RPWD), pp. 271–275.
ICPRICPR-1996-HoK #complexity
Building projectable classifiers of arbitrary complexity (TKH, EMK), pp. 880–885.
ICPRICPR-1996-HolmstromKLO #network #statistics
Neural network and statistical perspectives of classification (LH, PK, JL, EO), pp. 286–290.
ICPRICPR-1996-HuangLSSSLTH #approach #nearest neighbour #prototype
A simulated annealing approach to construct optimized prototypes for nearest-neighbor classification (YSH, KL, CYS, AJS, IIS, MCL, RYT, PKH), pp. 483–487.
ICPRICPR-1996-HwangB #network #performance #recognition
An efficient method to construct a radial basis function neural network classifier and its application to unconstrained handwritten digit recognition (YSH, SYB), pp. 640–644.
ICPRICPR-1996-JozwikCCS #fuzzy
A 1-NN preclassifier for fuzzy k-NN rule (AJ, LC, WC, MS), pp. 234–238.
ICPRICPR-1996-KalviainenBPK #random
Mixed pixel classification with the randomized Hough transform (HK, PB, MP, JK), pp. 576–580.
ICPRICPR-1996-KauppinenS #fault
The effect of illumination variations on color-based wood defect classification (HK, OS), pp. 828–832.
ICPRICPR-1996-KindratenkoE #fourier #using
Classification of irregularly shaped micro-objects using complex Fourier descriptors (VVK, PJMVE), pp. 285–289.
ICPRICPR-1996-KitamotoT #image #probability
A stochastic model of mixels and image classification (AK, MT), pp. 745–749.
ICPRICPR-1996-KittlerHD
Combining classifiers (JK, MH, RPWD), pp. 897–901.
ICPRICPR-1996-KrzyzakL #complexity #convergence #network #parametricity
Radial basis function networks and nonparametric classification: complexity regularization and rates of convergence (AK, TL), pp. 650–653.
ICPRICPR-1996-KudoS #using
Selection of classifiers based on the MDL principle using the VC dimension (MK, MS), pp. 886–890.
ICPRICPR-1996-LaferteHP #algorithm #image #multi
A multiresolution EM algorithm for unsupervised image classification (JML, FH, PP), pp. 849–853.
ICPRICPR-1996-LernerGADR #feature model #network
Feature extraction by neural network nonlinear mapping for pattern classification (BL, HG, MA, ID, YR), pp. 320–324.
ICPRICPR-1996-LiuL #approach #effectiveness #performance #using
An efficient and effective texture classification approach using a new notion in wavelet theory (JFL, JCML), pp. 820–824.
ICPRICPR-1996-MaioM #approach
A structural approach to fingerprint classification (DM, DM), pp. 578–585.
ICPRICPR-1996-MurshedBS #approach #detection #fuzzy #problem
A fuzzy ARTMAP-based classification system for detecting cancerous cells, based on the one-class problem approach (NAM, FB, RS), pp. 478–482.
ICPRICPR-1996-PeuraVK #approach
A new approach to land-based cloud classification (MP, AV, PK), pp. 143–147.
ICPRICPR-1996-PietikainenNMO
Accurate color discrimination with classification based on feature distributions (MP, SN, EM, TO), pp. 833–838.
ICPRICPR-1996-Raudys #design #linear
Linear classifiers in perceptron design (SR), pp. 763–767.
ICPRICPR-1996-RaudysD #empirical #fault
Expected error of minimum empirical error and maximal margin classifiers (SR, VD), pp. 875–879.
ICPRICPR-1996-RoliSB #image #multi #network
Classification of multisensor remote-sensing images by multiple structured neural networks (FR, SBS, LB), pp. 180–184.
ICPRICPR-1996-Skubalska-RafajlowiczK #metric #performance #using
Fast k-NN classification rule using metric on space-filling curves (ESR, AK), pp. 121–125.
ICPRICPR-1996-SkurichinaD
Stabilizing classifiers for very small sample sizes (MS, RPWD), pp. 891–896.
ICPRICPR-1996-Solberg #analysis #flexibility
Texture fusion and classification based on flexible discriminant analysis (AHSS), pp. 596–600.
ICPRICPR-1996-StockerRLE #distributed #incremental
Incremental distributed classifier building (ES, AR, YL, AE), pp. 128–132.
ICPRICPR-1996-SzeL #algorithm #bound #branch
Branch and bound algorithm for the Bayes classifier (LS, CHL), pp. 705–709.
ICPRICPR-1996-TingL #string #using
Business form classification using strings (AT, MKHL), pp. 690–694.
ICPRICPR-1996-TumerG #fault
Estimating the Bayes error rate through classifier combining (KT, JG), pp. 695–699.
ICPRICPR-1996-VriesengaS #linear #modelling
Neural modeling of piecewise linear classifiers (MV, JS), pp. 281–285.
ICPRICPR-1996-WouwerSD #analysis #speech
Wavelet-FILVQ classifier for speech analysis (GVdW, PS, DVD), pp. 214–218.
ICPRICPR-1996-Yoshii #architecture
Pyramid architecture classification tree (HY), pp. 310–314.
ICPRICPR-1996-ZhangHG #image #knowledge-based #monitoring
Knowledge-based classification of CZCS images and monitoring of red tides off the west Florida shelf (MZ, LOH, DBG), pp. 452–456.
KDDKDD-1996-Kohavi #hybrid #scalability
Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid (RK), pp. 202–207.
KDDKDD-1996-Sahami #dependence #learning
Learning Limited Dependence Bayesian Classifiers (MS), pp. 335–338.
KDDKDD-1996-ShanZHC #database #set #using
Discovering Classification Knowledge in Databases Using Rough Sets (NS, WZ, HJH, NC), pp. 271–274.
KRKR-1996-JonssonDB #algebra #subclass
Tractable Subclasses of the Point-Interval Algebra: A Complete Classification (PJ, TD, CB), pp. 352–363.
SIGIRSIGIR-1996-LarkeyC #categorisation
Combining Classifiers in Text Categorization (LSL, WBC), pp. 289–297.
SIGIRSIGIR-1996-LewisSCP #algorithm #linear
Training Algorithms for Linear Text Classifiers (DDL, RES, JPC, RP), pp. 298–306.
SACSAC-1996-HarangsriSN #multi #optimisation #query #using
Query optimisation in multidatabase systems using query classification (BH, JS, AHHN), pp. 173–177.
SACSAC-1996-HasemiPAHP #approach #search-based
A rough-genetic approach for classification of complex data (RH, BAP, RBA, WGH, MGP), pp. 282–288.
PDPPDP-1996-RiedlR #algorithm
Classification of Load Distribution Algorithms (RR, LR), pp. 404–413.
ICDARICDAR-v1-1995-BunkeL #documentation #parsing #using
Classification and postprocessing of documents using an error-correcting parser (HB, RL), pp. 222–226.
ICDARICDAR-v1-1995-CaoSA #fuzzy
Fusion of classifiers with fuzzy integrals (JC, MS, MA), pp. 108–111.
ICDARICDAR-v1-1995-HongLHS #design #nearest neighbour #recognition
The design of a nearest-neighbor classifier and its use for Japanese character recognition (TH, SWKL, JJH, SNS), pp. 270–273.
ICDARICDAR-v1-1995-KimD #distance #network #recognition #using
Off-line Recognition of Korean Scripts Using Distance Matching and Neural Network Classifiers (SHK, JID), pp. 34–37.
ICDARICDAR-v1-1995-LeeS #approach #formal method #network
A theory of classifier combination: the neural network approach (DSL, SNS), pp. 42–45.
ICDARICDAR-v1-1995-SabourinG #approach #evaluation #multi #verification
An extended-shadow-code based approach for off-line signature verification. II. Evaluation of several multi-classifier combination strategies (RS, GG), pp. 197–201.
ICDARICDAR-v1-1995-StrathyS #multi #network
A two-stage multi-network OCR system with a soft pre-classifier and a network selector (NWS, CYS), pp. 78–81.
ICDARICDAR-v1-1995-Summers #documentation
Near-wordless document structure classification (KMS), pp. 462–465.
ICDARICDAR-v1-1995-TingLHC
A syntactic business form classifier (AT, MKHL, SCH, KYC), pp. 301–304.
ICDARICDAR-v1-1995-UtschickNKSN #evaluation #feature model #network
The evaluation of feature extraction criteria applied to neural network classifiers (WU, PN, CK, AS, JAN), pp. 315–318.
ICDARICDAR-v2-1995-AntonacopoulosR #representation #using
Representation and classification of complex-shaped printed regions using white tiles (AA, RTR), pp. 1132–1135.
ICDARICDAR-v2-1995-DengelD #approach #clustering #documentation #machine learning
Clustering and classification of document structure-a machine learning approach (AD, FD), pp. 587–591.
ICDARICDAR-v2-1995-DrouhardSG #case study #comparative #nearest neighbour #network #using #verification
Comparative study of the k nearest neighbour, threshold and neural network classifiers for handwritten signature verification using an enhanced directional PDF (JPD, RS, MG), pp. 807–810.
ICDARICDAR-v2-1995-JungN #design
Joint feature and classifier design for OCR (DMJ, GN), pp. 1115–1118.
ICDARICDAR-v2-1995-MadhvanathG #recognition #word
Serial classifier combination for handwritten word recognition (SM, VG), pp. 911–914.
ICDARICDAR-v2-1995-MatsunagaK #case study #learning #statistics
An experimental study of learning curves for statistical pattern classifiers (TM, HK), pp. 1103–1106.
ICDARICDAR-v2-1995-SauvolaP #analysis #feature model #performance #segmentation #using
Page segmentation and classification using fast feature extraction and connectivity analysis (JJS, MP), pp. 1127–1131.
ICDARICDAR-v2-1995-SivaramakrishnanPHSH #documentation #generative #using
Zone classification in a document using the method of feature vector generation (RS, ITP, JH, SS, RMH), pp. 541–544.
ICDARICDAR-v2-1995-TaylorLN #composition #documentation #functional
Classification and functional decomposition of business documents (SLT, ML, RWN), pp. 563–566.
ICDARICDAR-v2-1995-WangW #multi #recognition
A multi-layer classifier for recognition of unconstrained handwritten numerals (GEW, JFW), pp. 849–852.
ICDARICDAR-v2-1995-ZhouHL #recognition
A method of Jia Gu Wen recognition based on a two-level classification (XLZ, XCH, FL), pp. 833–836.
VLDBVLDB-1995-TreschPL #documentation
Type Classification of Semi-Structured Documents (MT, NP, AL), pp. 263–274.
WCREWCRE-1995-LakhotiaG #evaluation #towards
Toward Experimental Evaluation of Subsystem Classification Recovery Techniques (AL, JMG), pp. 262–269.
CIKMCIKM-1995-TreschL #documentation
An Extensible Classifier for Semi-Structured Documents (MT, AL), pp. 226–233.
ICMLICML-1995-DaganE #probability
Committee-Based Sampling For Training Probabilistic Classifiers (ID, SPE), pp. 150–157.
ICMLICML-1995-Drakopoulos #bound #fault #nearest neighbour
Bounds on the Classification Error of the Nearest Neighbor Rule (JAD), pp. 203–208.
ICMLICML-1995-Lubinsky #consistency #performance #using
Increasing the Performance and Consistency of Classification Trees by Using the Accuracy Criterion at the Leaves (DJL), pp. 371–377.
ICMLICML-1995-SinghP #algorithm #comparison #induction
A Comparison of Induction Algorithms for Selective and non-Selective Bayesian Classifiers (MS, GMP), pp. 497–505.
ICMLICML-1995-SmythGF #estimation #kernel #using
Retrofitting Decision Tree Classifiers Using Kernel Density Estimation (PS, AGG, UMF), pp. 506–514.
KDDKDD-1995-HastieT #adaptation #nearest neighbour
Discriminant Adaptive Nearest Neighbor Classification (TH, RT), pp. 142–149.
KDDKDD-1995-Pazzani #approach
An Iterative Improvement Approach for the Discretization of Numeric Attributes in Bayesian Classifiers (MJP), pp. 228–233.
SEKESEKE-1995-Borstler #feature model #reuse
Feature-Oriented Classification for Software Reuse (JB), pp. 204–211.
SIGIRSIGIR-1995-Lewis #optimisation
Evaluating and Optimizing Autonomous Text Classification Systems (DDL), pp. 246–254.
SIGIRSIGIR-1995-Riloff #difference #word
Little Words Can Make a Big Difference for Text Classification (ER), pp. 130–136.
SIGIRSIGIR-1995-SchutzeHP #comparison #documentation #problem
A Comparison of Classifiers and Document Representations for the Routing Problem (HS, DAH, JOP), pp. 229–237.
AdaEuropeAdaEurope-1995-Kempe #ada #data type #semistructured data
Heterogeneous Data Structures and Cross-Classification of Objects with Ada95 (MK), pp. 71–80.
RERE-1995-Zave #requirements #research
Classification of research efforts in requirements engineering (PZ), pp. 214–216.
ASEKBSE-1995-PenixBA #component #retrieval #reuse #semantics #using
Classification and Retrieval of Reusable Components Using Semantic Features (JP, PB, PA), pp. 131–138.
SACSAC-1995-HalgamugeBG #algorithm #comparison #generative #heuristic #rule-based #search-based
Comparison of a heuristic method with a genetic algorithm for generation of compact rule based classifiers (SKH, AB, MG), pp. 580–585.
SACSAC-1995-NauckK #approach
NEFCLASSmdash;a neuro-fuzzy approach for the classification of data (DN, RK), pp. 461–465.
SACSAC-1995-Stegmaier-StraccaT #detection #fuzzy #using
Cough detection using fuzzy classification (PASS, NNTG), pp. 440–444.
SACSAC-1995-Tschichold-Gurman #fuzzy #generative #incremental #learning #using
Generation and improvement of fuzzy classifiers with incremental learning using fuzzy RuleNet (NNTG), pp. 466–470.
CAiSECAiSE-1994-Odberg #database #evolution #flexibility #object-oriented
Category Classes: Flexible Classification and Evolution in Object-Oriented Databases (EO), pp. 406–420.
CIKMCIKM-1994-HeinleinKD #guidelines #representation
Representation of Medical Guidelines on Top of a Classification-Based System (CH, KK, PD), pp. 415–422.
CIKMCIKM-1994-RoseG #database
Hierarchical Classification as an Aid to Database and Hit-List Browsing (JRR, JG), pp. 408–414.
CIKMCIKM-1994-Rundensteiner #algorithm #object-oriented
A Classification Algorithm for Supporting Object-Oriented Views (EAR), pp. 18–25.
ICMLICML-1994-PazzaniMMAHB
Reducing Misclassification Costs (MJP, CJM, PMM, KMA, TH, CB), pp. 217–225.
SIGIRSIGIR-1994-Hoch #analysis #documentation #information retrieval #using
Using IR Techniques for Text Classification in Document Analysis (RH), pp. 31–40.
SIGIRSIGIR-1994-LewisG #algorithm
A Sequential Algorithm for Training Text Classifiers (DDL, WAG), pp. 3–12.
SACSAC-1994-AleshunasCB
Classification characteristics of SOM and ART2 (JJA, DCSC, WEB), pp. 297–302.
SACSAC-1994-FlachsbartBCH #algorithm #using
Using the ID3 symbolic classification algorithm to reduce data density (BF, WEB, DCSC, JH), pp. 292–296.
SACSAC-1994-GentherG #automation #clustering #fuzzy #generative #using
Automatic generation of a fuzzy classification system using fuzzy clustering methods (HG, MG), pp. 180–183.
SACSAC-1994-Konstam #algorithm #search-based #using
N-group classification using genetic algorithms (AHK), pp. 212–216.
SACSAC-1994-RitschelPG #multi #rating
Rating of pattern classifications in multi-layer perceptrons: theoretical background and practical results (WR, TP, RG), pp. 142–144.
SACSAC-1994-Sen
Representational effects in a simple classifier system (SS), pp. 206–211.
SACSAC-1994-Tschichold-Gurman #fuzzy #network
Fuzzy RuleNet: an artificial neural network model for fuzzy classification (NNTG), pp. 145–149.
DATEEDAC-1994-RobertGMT #design #geometry #realtime
Design of a Real Time Geometric Classifier (MR, PG, JM, ST), p. 656.
ICDARICDAR-1993-BayerK #segmentation
Cut classification for segmentation (TAB, UK), pp. 565–568.
ICDARICDAR-1993-CaesarGM93a #adaptation #scalability #set
Utilization of large disordered sample sets for classifier adaptation in complex domains (TC, JMG, EM), pp. 790–793.
ICDARICDAR-1993-DuneauD #recognition
An improved classification for cursive script recognition (LD, BD), pp. 842–845.
ICDARICDAR-1993-FrankeO #detection #statistics
Writing style detection by statistical combination of classifiers in form reader applications (JF, MFO), pp. 581–584.
ICDARICDAR-1993-HaoWN #analysis #approach #documentation #layout #segmentation
Nested segmentation: an approach for layout analysis in document classification (XH, JTLW, PAN), pp. 319–322.
ICDARICDAR-1993-HuangS #metric #multi
Combination of multiple classifiers with measurement values (YSH, CYS), pp. 598–601.
ICDARICDAR-1993-ImadeTW #documentation #image #network #segmentation #using
Segmentation and classification for mixed text/image documents using neural network (SI, ST, TW), pp. 930–934.
ICDARICDAR-1993-IwaneYI #analysis #approach #documentation #functional #image #layout
A functional classification approach to layout analysis of document images (KI, MY, OI), pp. 778–781.
ICDARICDAR-1993-IwataM #algorithm
A color classification algorithm (KI, GM), pp. 726–729.
ICDARICDAR-1993-NakajimaM #modelling #recognition
A model-based classifier in a scheme of recognition filter (YN, SM), pp. 68–71.
ICDARICDAR-1993-PlessisSHMLDM #multi #recognition #word
A multi-classifier combination strategy for the recognition of handwritten cursive words (BP, AS, LH, EM, EL, OD, JVM), pp. 642–645.
ICDARICDAR-1993-SabourinMTN #recognition
Classifier combination for hand-printed digit recognition (MS, AM, DST, GN), pp. 163–166.
ICDARICDAR-1993-Yan #design #implementation #nearest neighbour #recognition
Design and implementation of optimized nearest neighbor classifiers for handwritten digit recognition (HY), pp. 10–13.
ICDARICDAR-1993-Yan93a #image #nearest neighbour #segmentation #using
Color map image segmentation using optimized nearest neighbor classifiers (HY), pp. 111–114.
ICDARICDAR-1993-ZidouriCS #documentation #image
Classification of compound document image patterns by MCR stroke index (ABCZ, SC, MS), pp. 753–756.
CIKMCIKM-1993-EickJ #algorithm #learning #search-based
Learning Bayesian Classification Rules through Genetic Algorithms (CFE, DJ), pp. 305–313.
CIKMCIKM-1993-Riloff #using
Using Cases to Represent Context for Text Classification (ER), pp. 105–113.
SEKESEKE-1993-LaiY #grid #multi #reuse #usability
Multi-Layer Repertory Grid Classification for Increasing Software Reusability (STL, CCY), pp. 252–254.
SEKESEKE-1993-Porter #component #predict
Developing and Analyzing Classification Rules for Predicting Faulty Software Components (AAP), pp. 453–461.
RERE-1993-BickertonS #requirements
The classification of requirements engineering methods (MJB, JS), pp. 182–186.
ICSEICSE-1993-Zelkowitz #using
Use of an Environment Classification Model (MVZ), pp. 348–357.
VLDBVLDB-1992-AgrawalGIIS #database #mining
An Interval Classifier for Database Mining Applications (RA, SPG, TI, BRI, ANS), pp. 560–573.
ICMLML-1992-HunterHS #performance
Efficient Classification of Massive, Unsegmented Datastreams (LH, NLH, DJS), pp. 224–232.
ICMLML-1992-Venturini #named
AGIL: Solving the Exploration Versus Exploration Dilemma in a single Classifier System Applied to Simulated Robotics (GV), pp. 458–463.
SIGIRSIGIR-1992-BlossevilleHMP #analysis #automation #documentation #natural language #statistics
Automatic Document Classification: Natural Language Processing, Statistical Analysis, and Expert System Techniques used together (MJB, GH, MGM, NP), pp. 51–58.
OOPSLAOOPSLA-1992-Yelland #smalltalk
Experimental Classification Facilities for Smalltalk (PMY), pp. 235–246.
TOOLSTOOLS-EUROPE-1992-KarlssonST #component #object-oriented #reuse
Classification of Object-Oriented Components for Reuse (EAK, LSS, ET), pp. 21–31.
KDDKDD-1991-ChanW #database #statistics
Statistical Technique for Extracting Classificatory Knowledge from Databases (KCCC, AKCW), pp. 107–124.
KDDKDD-1991-WuSO #heuristic #integration
Integration of Heuristic and Bayesian Approaches in a Pattern-Classification System (QW, PS, AO), pp. 249–260.
ICMLML-1991-BelyaevF
Noise-Resistant Classification (LVB, LPF), pp. 581–585.
ICMLML-1991-CrawfordFAT #information retrieval
Classification Trees for Information Retrieval (SLC, RMF, LAA, RMT), pp. 245–249.
POPLPOPL-1991-LandiR #alias #pointer #problem
Pointer-Induced Aliasing: A Problem Classification (WL, BGR), pp. 93–103.
ESECESEC-1991-SelbyM #analysis #metric
Metric-Driven Classification Analysis (RWS, RKM), pp. 290–307.
SEKESEKE-1990-EichmannA #design
Design of a Lattice-Based Faceted Classification System (DE, JA), pp. 90–97.
ICSEICSE-1990-Diaz #implementation #reuse
Implementing Faceted Classification for Software Reuse (RPD), pp. 300–304.
LICSLICS-1990-Jung
The Classification of Continuous Domains (AJ), pp. 35–40.
CAiSECAiSE-1989-HernbackL #analysis #automation #framework #implementation #tool support
A Framework for Use and Classification of CASE Tools in Systems Analysis and a Strategy for Implementation (JH, IL).
CAiSECAiSE-1989-Nilsson #development #information management
Information Systems Development: A Frame Of Reference and Classifications (AGN).
ICMLML-1989-Buntine #learning #using
Learning Classification Rules Using Bayes (WLB), pp. 94–98.
ICMLML-1989-HilliardLRP #approach #hybrid #learning #problem #scheduling
Learning Decision Rules for scheduling Problems: A Classifier Hybrid Approach (MRH, GEL, GR, MRP), pp. 188–190.
SIGIRSIGIR-1989-Kwasnik #documentation #how
How a Personal Document’s Intended Use or Purpose Affects its Classification in an Office (BHK), pp. 207–210.
SIGMODSIGMOD-1988-YounHH #database #deduction #recursion
Classification of Recursive Formulas in Deductive Databases (CY, LJH, JH), pp. 320–328.
ICMLML-1988-CheesemanKSSTF #named
AutoClass: A Bayesian Classification System (PC, JK, MS, JS, WT, DF), pp. 54–64.
ICMLML-1988-DavisY
Classifier Systems with Hamming Weights (LD, DKY), pp. 162–173.
ICMLML-1988-Quinlan #comparison #empirical #search-based
An Empirical Comparison of Genetic and Decision-Tree Classifiers (JRQ), pp. 135–141.
ICMLML-1988-Robertson
Population Size in classifier Systems (GGR), pp. 142–152.
ICMLML-1988-TanE #network #using
Using Weighted Networks to Represent Classification Knowledge in Noisy Domains (MT, LJE), pp. 121–134.
ECOOPECOOP-1988-Knudsen #multi
Name Collision in Multiple Classification Hierarchies (JLK), pp. 93–109.
ICLPJICSCP-1988-AptB88 #modelling #source code
Arithmetic Classification of Perfect Models of Stratified Programs (KRA, HAB), pp. 765–779.
ECOOPECOOP-1987-KristensenMMN #inheritance
Classification of Actions, or Inheritance also for Methods (BBK, OLM, BMP, KN), pp. 98–107.
ICALPICALP-1986-AverbuchWG #algorithm #polynomial
Classification of all the Minimal Bilinear Algorithms for Computing the Coefficients of the Product of Two Polynomials Modulo a Polynomial (AA, SW, ZG), pp. 31–39.
CADECADE-1986-Walther #problem #unification
A Classification of Many-Sorted Unification Problems (CW), pp. 525–537.
VLDBVLDB-1984-Woehl #automation #database #documentation #prolog #relational
Automatic Classification of Office Documents by Coupling Relational Data Bases and PROLOG Expert Systems (KW), pp. 529–532.
CADECADE-1982-SiekmannS #equation #unification
Universal Unification and a Classification of Equational Theories (JHS, PS), pp. 369–389.
SIGIRSIGIR-1981-Fraenkel #documentation #problem
Document Classification, Indexing and Abstracting May be Inherently Difficult Problems (ASF), pp. 77–82.
VLDBVLDB-1978-Ashany #analysis #database #matrix #retrieval #scalability
Application of Sparse Matrix Techniques to Search, Retrieval, Classification and Relationship Analysis in Large Data Base Systems — SPARCOM (RA), pp. 499–516.
DACDAC-1978-Harvel #effectiveness
Classification of PCB types for cost effective solutions (JTH), pp. 444–445.
SIGIRSIGIR-1971-Jackson
Optimal Classification and Its Consequences (DMJ), pp. 217–224.
STOCSTOC-1971-Machtey #recursion
Classification of Computable Functions by Primitive Recursive Classes (MM), pp. 251–257.

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