BibSLEIGH
BibSLEIGH corpus
BibSLEIGH tags
BibSLEIGH bundles
BibSLEIGH people
CC-BY
Open Knowledge
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Used together with:
base (452)
use (411)
select (330)
model (277)
recognit (234)

Stem featur$ (all stems)

2176 papers:

ECSAECSA-2015-TahriDP #architecture #deployment #distributed #feature model #modelling #smarttech #using
Using Feature Models for Distributed Deployment in Extended Smart Home Architecture (AT, LD, JP), pp. 285–293.
QoSAQoSA-2015-DurisicST #architecture #identification #set #standard
Identifying Optimal Sets of Standardized Architectural Features: A Method and its Automotive Application (DD, MS, MT), pp. 103–112.
CASECASE-2015-LiYTC #architecture #fault
Extracting relevant features for diagnosing machine tool faults in cloud architecture (YYL, HCY, HT, FTC), pp. 1434–1439.
DACDAC-2015-JiangLZYW #effectiveness #feature model #image #performance
A 127 fps in full hd accelerator based on optimized AKAZE with efficiency and effectiveness for image feature extraction (GJ, LL, WZ, SY, SW), p. 6.
DACDAC-2015-JiangWS #clustering #power management #sorting
A low power unsupervised spike sorting accelerator insensitive to clustering initialization in sub-optimal feature space (ZJ, QW, MS), p. 6.
DACDAC-2015-KrishnaNRT #analysis #composition #modelling #product line
Compositional modeling and analysis of automotive feature product lines (SNK, GKN, SR, AT), p. 6.
DATEDATE-2015-BarraganL #case study #feature model #using
Feature selection for alternate test using wrappers: application to an RF LNA case study (MJB, GL), pp. 1229–1232.
DATEDATE-2015-CaoBFCCAO #feature model #validation
LVS check for photonic integrated circuits: curvilinear feature extraction and validation (RC, JB, JF, LC, JC, AA, IO), pp. 1253–1256.
DATEDATE-2015-StoppeWD #automation #design #locality
Automated feature localization for dynamically generated SystemC designs (JS, RW, RD), pp. 277–280.
DRRDRR-2015-MiouletBCPB #architecture #multi #network #recognition
Exploring multiple feature combination strategies with a recurrent neural network architecture for off-line handwriting recognition (LM, GB, CC, TP, SB).
HTHT-2015-PeraN #recommendation
Analyzing Book-Related Features to Recommend Books for Emergent Readers (MSP, YKN), pp. 221–230.
ICPCICPC-2015-BeckDVWP #feature model #user interface
Rethinking user interfaces for feature location (FB, BD, JVM, DW, DP), pp. 151–162.
ICPCICPC-2015-HillSP #evaluation #feature model
Exploring the use of concern element role information in feature location evaluation (EH, DCS, LLP), pp. 140–150.
ICPCICPC-2015-JordanRHBB #feature model #industrial #source code
Manually locating features in industrial source code: the search actions of software nomads (HRJ, JR, SH, GB, JB), pp. 174–177.
ICPCICPC-2015-MartinCAA #analysis #empirical #open source
Make it simple: an empirical analysis of GNU make feature use in open source projects (DHM, JRC, BA, GA), pp. 207–217.
ICSMEICSME-2015-CorleyDK #feature model #learning
Exploring the use of deep learning for feature location (CSC, KD, NAK), pp. 556–560.
ICSMEICSME-2015-CorleyKK #feature model #modelling #topic
Modeling changeset topics for feature location (CSC, KLK, NAK), pp. 71–80.
ICSMEICSME-2015-GaoH #architecture #named #web
ArchFLoc: Locating and explaining architectural features in running web applications (YG, DH), pp. 333–335.
ICSMEICSME-2015-LeLL #fault #feature model
Constrained feature selection for localizing faults (TDBL, DL, ML), pp. 501–505.
SANERSANER-2015-LianZ #feature model #non-functional #product line #requirements #towards
Optimized feature selection towards functional and non-functional requirements in Software Product Lines (XL, LZ), pp. 191–200.
SCAMSCAM-2015-ChochlovEB #data flow #feature model #using
Using changeset descriptions as a data source to assist feature location (MC, ME, JB), pp. 51–60.
LATALATA-2015-Yoshinaka #boolean grammar #grammar inference #learning
Learning Conjunctive Grammars and Contextual Binary Feature Grammars (RY), pp. 623–635.
FMFM-2015-SafilianMD #feature model #formal method #modelling #semantics
The Semantics of Cardinality-Based Feature Models via Formal Languages (AS, TSEM, ZD), pp. 453–469.
SEFMSEFM-2015-BeekDGMP #constraints #variability
From Featured Transition Systems to Modal Transition Systems with Variability Constraints (MHtB, FD, SG, FM, LP), pp. 344–359.
ICFPICFP-2015-ZilianiS #algorithm #coq #morphism #polymorphism #unification
A unification algorithm for Coq featuring universe polymorphism and overloading (BZ, MS), pp. 179–191.
ICGTICGT-2015-BurUHV #pattern matching #search-based
Local Search-Based Pattern Matching Features in EMF-IncQuery (MB, ZU, ÁH, DV), pp. 275–282.
CHICHI-2015-ButlerASGP #analysis #automation #design #game studies
Automatic Game Progression Design through Analysis of Solution Features (EB, EA, AMS, SG, ZP), pp. 2407–2416.
CSCWCSCW-2015-DasKDH #security #social
The Role of Social Influence in Security Feature Adoption (SD, ADIK, LAD, JIH), pp. 1416–1426.
HCIDUXU-IXD-2015-GomesFL
Antique School Furniture, New Technological Features Needs (AG, EF, LL), pp. 185–196.
HCIDUXU-UI-2015-LinL15b #design
Affordances Feature on Package Design has Preference Effect on Content (JL, CHL), pp. 87–94.
HCIHCI-IT-2015-MullerLBSKSW #bibliography #data-driven #network #predict #using
Using Neural Networks for Data-Driven Backchannel Prediction: A Survey on Input Features and Training Techniques (MM, DL, LB, MS, KK, SS, AW), pp. 329–340.
HCIHCI-UC-2015-AlexandrisNC #evaluation #interactive
Interactive Evaluation of Pragmatic Features in Spoken Journalistic Texts (CA, MN, GC), pp. 259–268.
HCIHIMI-IKC-2015-ZengCLSHC #framework #mobile #query
Scene Feature Recognition-Enabled Framework for Mobile Service Information Query System (YCZ, YHC, TYL, MJS, PYH, GLC), pp. 64–74.
HCIHIMI-IKD-2015-ChangH15a #case study
A Study of the Feature of the Lovely Product Forms (WcC, CAH), pp. 571–581.
HCIHIMI-IKD-2015-ProssHTH #concept #interactive #visualisation
A Concept for Visualizing Psychophysiological Data in Human Computer Interaction: The FeaturePlotter (FP, DH, HCT, HH), pp. 97–106.
ICEISICEIS-v2-2015-TangL #framework #mining #product line #top-down
Top-down Feature Mining Framework for Software Product Line (YT, HL), pp. 71–81.
ECIRECIR-2015-HuynhHR #analysis #learning #sentiment #strict
Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis (TH, YH, SMR), pp. 447–452.
ECIRECIR-2015-SchindlerR #approach #classification #music
An Audio-Visual Approach to Music Genre Classification through Affective Color Features (AS, AR), pp. 61–67.
ICMLICML-2015-Hernandez-Lobato #feature model #multi #probability
A Probabilistic Model for Dirty Multi-task Feature Selection (DHL, JMHL, ZG), pp. 1073–1082.
ICMLICML-2015-LongC0J #adaptation #learning #network
Learning Transferable Features with Deep Adaptation Networks (ML, YC, JW, MJ), pp. 97–105.
ICMLICML-2015-NanWS #random
Feature-Budgeted Random Forest (FN, JW, VS), pp. 1983–1991.
ICMLICML-2015-WangY #learning #matrix #multi
Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices (JW, JY), pp. 1747–1756.
ICMLICML-2015-XiaoBBFER #feature model #question
Is Feature Selection Secure against Training Data Poisoning? (HX, BB, GB, GF, CE, FR), pp. 1689–1698.
KDDKDD-2015-DuS #adaptation #feature model #learning
Unsupervised Feature Selection with Adaptive Structure Learning (LD, YDS), pp. 209–218.
KDDKDD-2015-GaoYCH #integration #learning #multi #visual notation
Anatomical Annotations for Drosophila Gene Expression Patterns via Multi-Dimensional Visual Descriptors Integration: Multi-Dimensional Feature Learning (HG, LY, WC, HH), pp. 339–348.
KDDKDD-2015-KotziasDFS #using
From Group to Individual Labels Using Deep Features (DK, MD, NdF, PS), pp. 597–606.
KDDKDD-2015-XuSB #learning #predict
Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction (TX, JS, JB), pp. 1345–1354.
MLDMMLDM-2015-PatchalaBG #email #using
Author Attribution of Email Messages Using Parse-Tree Features (JP, RB, SG), pp. 313–327.
MLDMMLDM-2015-Perner #automation #feature model #image #mining
Automatic Cell Tracking and Kinetic Feature Description of Cell Paths for Image Mining (PP), pp. 441–451.
RecSysRecSys-2015-MouliC #dependence #feedback #modelling
Making the Most of Preference Feedback by Modeling Feature Dependencies (SCM, SC), pp. 285–288.
RecSysRecSys-2015-SongCL #incremental #matrix #recommendation
Incremental Matrix Factorization via Feature Space Re-learning for Recommender System (QS, JC, HL), pp. 277–280.
SEKESEKE-2015-GaoKN #set
Combining Feature Subset Selection and Data Sampling for Coping with Highly Imbalanced Software Data (KG, TMK, AN), pp. 439–444.
SEKESEKE-2015-PereiraSA #interface #sql #standard
Endowing NoSQL DBMS with SQL Features Through Standard Call Level Interfaces (ÓMP, DS, RLA), pp. 201–207.
SEKESEKE-2015-TaheriS #agile #classification #development
A Feature-Based Tool-Selection Classification for Agile Software Development (MT, SMS), pp. 700–704.
SEKESEKE-2015-WangCMCX #empirical #python
An empirical study on the impact of Python dynamic features on change-proneness (BW, LC, WM, ZC, BX), pp. 134–139.
SEKESEKE-2015-WangKN #feature model #re-engineering
Stability of Three Forms of Feature Selection Methods on Software Engineering Data (HW, TMK, AN), pp. 385–390.
SEKESEKE-2015-ZouCH #impact analysis #mobile #topic #user interface
Topic Matching Based Change Impact Analysis from Feature on User Interface of Mobile Apps (QZ, XC, YH), pp. 477–482.
SIGIRSIGIR-2015-CanutoGSRM #approach #classification #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-GuoL #automation #generative #graph #music #recommendation
Automatic Feature Generation on Heterogeneous Graph for Music Recommendation (CG, XL), pp. 807–810.
SIGIRSIGIR-2015-JonesTSS #effectiveness #metric #retrieval
Features of Disagreement Between Retrieval Effectiveness Measures (TJ, PT, FS, MS), pp. 847–850.
SIGIRSIGIR-2015-LuccheseNOPT #documentation #ranking
Speeding up Document Ranking with Rank-based Features (CL, FMN, SO, RP, NT), pp. 895–898.
MoDELSMoDELS-2015-LettnerEGP #case study #experience #feature model #industrial #lessons learnt #modelling #scalability
Feature modeling of two large-scale industrial software systems: Experiences and lessons learned (DL, KE, PG, HP), pp. 386–395.
REFSQREFSQ-2015-OliinykPSBS #case study #evaluation #feature model #industrial #metric #modelling
Metrics for the Evaluation of Feature Models in an Industrial Context: A Case Study at Opel (OO, KP, MS, MB, SS), pp. 33–48.
SACSAC-2015-BarbieriTPG #named #representation #video #visual notation
Shot-HR: a video shot representation method based on visual features (TTSB, THT, MPPJ, RG), pp. 1257–1262.
SACSAC-2015-BerardiEF015a #case study #design #industrial
Classifying websites by industry sector: a study in feature design (GB, AE, TF, FS), pp. 1053–1059.
SACSAC-2015-JavedSBJ #feature model #robust
OR-PCA with dynamic feature selection for robust background subtraction (SJ, AS, TB, SKJ), pp. 86–91.
SACSAC-2015-MeftehBB #approach #case study #diagrams #evaluation #feature model #implementation #modelling #uml
Implementation and evaluation of an approach for extracting feature models from documented UML use case diagrams (MM, NB, HBA), pp. 1602–1609.
SACSAC-2015-SeifertSG #personalisation #set #towards
Towards a feature-rich data set for personalized access to long-tail content (CS, JS, MG), pp. 1031–1038.
SLESLE-2015-OchoaRT #feature model #modelling #using
Using decision rules for solving conflicts in extended feature models (LO, OGR, TT), pp. 149–160.
SPLCSPLC-2015-BecanBGA #feature model #modelling #synthesis
Synthesis of attributed feature models from product descriptions (GB, RB, AG, MA), pp. 1–10.
SPLCSPLC-2015-BergerLRGS0CC #industrial #product line #what
What is a feature?: a qualitative study of features in industrial software product lines (TB, DL, JR, PG, AS, MB, MC, KC), pp. 16–25.
SPLCSPLC-2015-Beuche #feature model #modelling #variability
Managing variability with feature models (DB), p. 386.
SPLCSPLC-2015-ChavarriagaRNCJ #case study #configuration management #experience #feature model #modelling #multi #using
Using multiple feature models to specify configuration options for electrical transformers: an experience report (JC, CR, CN, RC, VJ), pp. 216–224.
SPLCSPLC-2015-DudderRH #composition #design #staged #type safety #using
Synthesizing type-safe compositions in feature oriented software designs using staged composition (BD, JR, GTH), pp. 398–401.
SPLCSPLC-2015-FerrariSGD #diagrams #documentation #feature model #natural language #tool support
CMT and FDE: tools to bridge the gap between natural language documents and feature diagrams (AF, GOS, SG, FD), pp. 402–410.
SPLCSPLC-2015-JiBAC #embedded #maintenance #traceability
Maintaining feature traceability with embedded annotations (WJ, TB, MA, KC), pp. 61–70.
SPLCSPLC-2015-LiangGCR #analysis #feature model #modelling #satisfiability #scalability
SAT-based analysis of large real-world feature models is easy (JH(L, VG, KC, VR), pp. 91–100.
SPLCSPLC-2015-ReulingBRLK #effectiveness #generative #product line #testing
Fault-based product-line testing: effective sample generation based on feature-diagram mutation (DR, JB, SR, ML, UK), pp. 131–140.
SPLCSPLC-2015-SoutoGdMKB #debugging #detection #feature model #modelling #performance #product line
Faster bug detection for software product lines with incomplete feature models (SS, DG, Md, DM, SK, DSB), pp. 151–160.
CCCC-2015-St-AmourAF #feature model #profiling
Feature-Specific Profiling (VSA, LA, MF), pp. 49–68.
ICSTICST-2015-ArcainiGV #detection #fault #feature model #generative #modelling #testing
Generating Tests for Detecting Faults in Feature Models (PA, AG, PV), pp. 1–10.
ISSTAISSTA-2015-Hothersall-Thomas #automation #named #security #testing
BrowserAudit: automated testing of browser security features (CHT, SM, CN), pp. 37–47.
ISSTAISSTA-2015-TanXCSLD #algorithm #optimisation
Optimizing selection of competing features via feedback-directed evolutionary algorithms (THT, YX, MC, JS, YL, JSD), pp. 246–256.
QoSAQoSA-2014-EtxeberriaTCS #hardware #nondeterminism #parametricity
Performance-based selection of software and hardware features under parameter uncertainty (LE, CT, VC, GS), pp. 23–32.
ASEASE-2014-Burke #feature model
Utilizing feature location techniques for feature addition and feature enhancement (JTB), pp. 879–882.
ASEASE-2014-RahimiC #automation
Personas in the middle: automated support for creating personas as focal points in feature gathering forums (MR, JCH), pp. 479–484.
CASECASE-2014-LinWF #using
Grasping unknown objects using depth gradient feature with eye-in-hand RGB-D sensor (YCL, STW, LCF), pp. 1258–1263.
CASECASE-2014-TiengYHC #approach #multi #optimisation #process
A multi-objective optimization approach for selecting key features of machining processes (HT, HCY, MHH, FTC), pp. 899–904.
DACDAC-2014-TrimbergerM #security
FPGA Security: From Features to Capabilities to Trusted Systems (ST, JM), p. 4.
DATEDATE-2014-AbeleinCEGRGRTUW #architecture #integration
Non-intrusive integration of advanced diagnosis features in automotive E/E-architectures (UA, AC, PE, MG, FR, LRG, TR, JT, DU, HJW), pp. 1–6.
DATEDATE-2014-FerentD #comparison #mining #novel #synthesis #using
Novel circuit topology synthesis method using circuit feature mining and symbolic comparison (CF, AD), pp. 1–4.
DocEngDocEng-2014-MartinsP #documentation #multi #named #reuse
ActiveTimesheets: extending web-based multimedia documents with dynamic modification and reuse features (DSM, MdGCP), pp. 3–12.
DRRDRR-2014-KleberDS #classification #retrieval #using #word
Form classification and retrieval using bag of words with shape features of line structures (FK, MD, RS), pp. 902107–9.
HTHT-2014-Santos-NetoPAR #data flow #on the #optimisation
On the choice of data sources to improve content discoverability via textual feature optimization (ESN, TP, JMA, MR), pp. 273–278.
SIGMODSIGMOD-2014-ZhangKR #feature model #optimisation
Materialization optimizations for feature selection workloads (CZ, AK, CR), pp. 265–276.
VLDBVLDB-2014-AndersonCJWZ #development #ide #performance #re-engineering
An Integrated Development Environment for Faster Feature Engineering (MRA, MJC, YJ, GW, BZ), pp. 1657–1660.
SANERCSMR-WCRE-2014-LammelLSV #comparison #implementation
Comparison of feature implementations across languages, technologies, and styles (RL, ML, TS, AV), pp. 333–337.
ICPCICPC-2014-VasconcelosSW #feature model #visualisation
An information visualization feature model for supporting the selection of software visualizations (RV, MS, CW), pp. 122–125.
ICSMEICSME-2014-EderFHJ #question
Which Features Do My Users (Not) Use? (SE, HF, BH, MJ), pp. 446–450.
ICSMEICSME-2014-LinsbauerAGLPLE #variability
Recovering Feature-to-Code Mappings in Mixed-Variability Software Systems (LL, FA, PG, DL, HP, RELH, AE), pp. 426–430.
MSRMSR-2014-AkerblomSTW #python #source code
Tracing dynamic features in python programs (, JS, MT, TW), pp. 292–295.
MSRMSR-2014-KleinCK #debugging #detection
New features for duplicate bug detection (NK, CSC, NAK), pp. 324–327.
MSRMSR-2014-KochharLL #classification #debugging #locality #question
It’s not a bug, it’s a feature: does misclassification affect bug localization? (PSK, TDBL, DL), pp. 296–299.
MSRMSR-2014-PassosC #dataset #feature model #kernel #linux
A dataset of feature additions and feature removals from the Linux kernel (LTP, KC), pp. 376–379.
CHICHI-2014-HarpsteadMAM #design #education #game studies #using
Using extracted features to inform alignment-driven design ideas in an educational game (EH, CJM, VA, BAM), pp. 3329–3338.
CHICHI-2014-SchwarzXMHH #classification #probability #using
Probabilistic palm rejection using spatiotemporal touch features and iterative classification (JS, RX, JM, SEH, CH), pp. 2009–2012.
HCIDHM-2014-TakaiYGWI #case study #comparative
Comparative Study on the Feature of Kitchen Knife Sharpening Skill between Expert and Non-Expert (YT, MY, AG, ZW, AI), pp. 292–300.
HCIDUXU-DI-2014-HeZL #detection #fault #feature model #image #segmentation
Aluminum CT Image Defect Detection Based on Segmentation and Feature Extraction (NH, LZ, KL), pp. 446–454.
HCIDUXU-DI-2014-ShafiqICRAAR #analysis #case study #learning #smarttech #usability #user satisfaction #what
To What Extent System Usability Effects User Satisfaction: A Case Study of Smart Phone Features Analysis for Learning of Novice (MS, MI, JGC, ZR, MA, WA, SR), pp. 346–357.
HCIHCI-AIMT-2014-MohammedSS #predict
Gaze Location Prediction with Depth Features as Auxiliary Information (RAAM, LS, OGS), pp. 281–292.
HCIHIMI-DE-2014-KhodaskarL #image #retrieval #semantics #using
Content Based Image Retrieval Using Quantitative Semantic Features (AK, SL), pp. 439–448.
HCISCSM-2014-AhangamaLKP #analysis #mobile #monitoring
Revolutionizing Mobile Healthcare Monitoring Technology: Analysis of Features through Task Model (SA, YSL, SYK, DCCP), pp. 298–305.
HCISCSM-2014-RoussakiKLJKRLA #pervasive #social #social media
Enhancing Social Media with Pervasive Features (IR, NK, NL, EJ, PK, MR, LL, MEA), pp. 265–276.
VISSOFTVISSOFT-2014-MartinezZMBKT #constraints #graph #paradigm #product line #visualisation
Feature Relations Graphs: A Visualisation Paradigm for Feature Constraints in Software Product Lines (JM, TZ, RM, TFB, JK, YLT), pp. 50–59.
EDOCEDOC-2014-WitternLBB #as a service #independence
Feature-Based Configuration of Vendor-Independent Deployments on IaaS (EW, AL, SB, TB), pp. 128–135.
CIKMCIKM-2014-CanutoSGRRGRM #classification #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-DavletovAC #predict #using
High Impact Academic Paper Prediction Using Temporal and Topological Features (FD, ASA, AC), pp. 491–498.
CIKMCIKM-2014-DeveaudAMO #learning #on the #rank
On the Importance of Venue-Dependent Features for Learning to Rank Contextual Suggestions (RD, MDA, CM, IO), pp. 1827–1830.
CIKMCIKM-2014-KangLSSK #coordination #distributed #probability
Data/Feature Distributed Stochastic Coordinate Descent for Logistic Regression (DK, WL, KS, LS, UK), pp. 1269–1278.
CIKMCIKM-2014-QianZ #clustering #feature model #multi #web
Unsupervised Feature Selection for Multi-View Clustering on Text-Image Web News Data (MQ, CZ), pp. 1963–1966.
CIKMCIKM-2014-UysalBSS #approximate #database #distance #multi #performance #scalability #using
Efficient Filter Approximation Using the Earth Mover’s Distance in Very Large Multimedia Databases with Feature Signatures (MSU, CB, JS, TS), pp. 979–988.
CIKMCIKM-2014-WuHPZCZ #feature model #learning #multi
Exploring Features for Complicated Objects: Cross-View Feature Selection for Multi-Instance Learning (JW, ZH, SP, XZ, ZC, CZ), pp. 1699–1708.
ECIRECIR-2014-NainiA #feature model #learning #rank
Exploiting Result Diversification Methods for Feature Selection in Learning to Rank (KDN, ISA), pp. 455–461.
ICMLICML-c1-2014-DonahueJVHZTD #named #recognition #visual notation
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition (JD, YJ, OV, JH, NZ, ET, TD), pp. 647–655.
ICMLICML-c1-2014-KarampatziakisM
Discriminative Features via Generalized Eigenvectors (NK, PM), pp. 494–502.
ICMLICML-c1-2014-YangSAM #invariant #kernel #monte carlo
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels (JY, VS, HA, MWM), pp. 485–493.
ICMLICML-c2-2014-HamidXGD #random
Compact Random Feature Maps (RH, YX, AG, DD), pp. 19–27.
ICMLICML-c2-2014-JawanpuriaVN #feature model #kernel #learning #multi #on the
On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection (PJ, MV, JSN), pp. 118–126.
ICMLICML-c2-2014-LinDH0 #classification #encoding #multi
Multi-label Classification via Feature-aware Implicit Label Space Encoding (ZL, GD, MH, JW), pp. 325–333.
ICPRICPR-2014-AlvaroSB #network
Offline Features for Classifying Handwritten Math Symbols with Recurrent Neural Networks (FA, JAS, JMB), pp. 2944–2949.
ICPRICPR-2014-BenliE #recognition
Extraction and Selection of Muscle Based Features for Facial Expression Recognition (KSB, MTE), pp. 1651–1656.
ICPRICPR-2014-BertoliniOJS #identification
Assessing Textural Features for Writer Identification on Different Writing Styles and Forgeries (DB, LSO, EJRJ, RS), pp. 268–272.
ICPRICPR-2014-BorgiLEA #named #performance #recognition
ShearFace: Efficient Extraction of Anisotropic Features for Face Recognition (MAB, DL, ME, CBA), pp. 1806–1811.
ICPRICPR-2014-BuoncompagniFM #recognition #sketching
Shape Features for Candidate Photo Selection in Sketch Recognition (SB, AF, DM), pp. 1728–1733.
ICPRICPR-2014-CetinaMB #case study #comparative #segmentation
A Comparative Study of Feature Descriptors for Mitochondria and Synapse Segmentation (KC, PMN, LB), pp. 3215–3220.
ICPRICPR-2014-ChenK #gesture #recognition #using
Using Appearance-Based Hand Features for Dynamic RGB-D Gesture Recognition (XC, MK), pp. 411–416.
ICPRICPR-2014-ChenYJ #analysis #feature model #linear #robust
An Improved Linear Discriminant Analysis with L1-Norm for Robust Feature Extraction (XC, JY, ZJ), pp. 1585–1590.
ICPRICPR-2014-ChernousovaLTMW #parametricity #validation
Non-enumerative Cross Validation for the Determination of Structural Parameters in Feature-Selective SVMs (EC, PL, AT, VM, DW), pp. 3654–3659.
ICPRICPR-2014-DavarzaniM #adaptation #image #robust
Robust Image Description with Weighted and Adaptive Local Binary Pattern Features (RD, SM), pp. 1097–1102.
ICPRICPR-2014-DengZS #learning #recognition #speech
Linked Source and Target Domain Subspace Feature Transfer Learning — Exemplified by Speech Emotion Recognition (JD, ZZ, BWS), pp. 761–766.
ICPRICPR-2014-DhamechaSSV #effectiveness #on the
On Effectiveness of Histogram of Oriented Gradient Features for Visible to Near Infrared Face Matching (TID, PS, RS, MV), pp. 1788–1793.
ICPRICPR-2014-DiezVPRB #optimisation #recognition
Optimizing PLLR Features for Spoken Language Recognition (MD, AV, MP, LJRF, GB), pp. 779–784.
ICPRICPR-2014-El-GaalyTE #classification
Spatial-Visual Label Propagation for Local Feature Classification (TEG, MT, AME), pp. 3422–3427.
ICPRICPR-2014-FradiD #detection #recognition
Sparse Feature Tracking for Crowd Change Detection and Event Recognition (HF, JLD), pp. 4116–4121.
ICPRICPR-2014-Garcia-OrdasAGG #invariant #named
aZIBO: A New Descriptor Based in Shape Moments and Rotational Invariant Features (MTGO, EA, VGC, DGO), pp. 2395–2400.
ICPRICPR-2014-GarciaMFGM #identification
Person Orientation and Feature Distances Boost Re-identification (JG, NM, GLF, AG, CM), pp. 4618–4623.
ICPRICPR-2014-Gonzalez-CastroDC #adaptation #classification #using
Pixel Classification Using General Adaptive Neighborhood-Based Features (VGC, JD, VC), pp. 3750–3755.
ICPRICPR-2014-Hast #invariant #robust
Robust and Invariant Phase Based Local Feature Matching (AH), pp. 809–814.
ICPRICPR-2014-HeDY0PJ #multi #random #using #visual notation
Visual Tracking Using Multi-stage Random Simple Features (YH, ZD, MY, LC, MP, YJ), pp. 4104–4109.
ICPRICPR-2014-HeS #identification #invariant
Delta-n Hinge: Rotation-Invariant Features for Writer Identification (SH, LS), pp. 2023–2028.
ICPRICPR-2014-HuangZLW #distance #feature model
A Method of Discriminative Information Preservation and In-Dimension Distance Minimization Method for Feature Selection (SH, JZ, XL, LW), pp. 1615–1620.
ICPRICPR-2014-KacheleS #independence #recognition #set
Cascaded Fusion of Dynamic, Spatial, and Textural Feature Sets for Person-Independent Facial Emotion Recognition (MK, FS), pp. 4660–4665.
ICPRICPR-2014-KacheleZMS #feature model #quality #recognition #using
Prosodic, Spectral and Voice Quality Feature Selection Using a Long-Term Stopping Criterion for Audio-Based Emotion Recognition (MK, DZ, SM, FS), pp. 803–808.
ICPRICPR-2014-KhanMMT #image
Emergent Properties from Feature Co-occurrence in Image Collections (UMK, SM, BM, AT), pp. 2347–2352.
ICPRICPR-2014-KrauseGDLF #fine-grained #learning #recognition
Learning Features and Parts for Fine-Grained Recognition (JK, TG, JD, LJL, FFL), pp. 26–33.
ICPRICPR-2014-KrawczykWC #classification #clustering #fuzzy
Weighted One-Class Classifier Ensemble Based on Fuzzy Feature Space Partitioning (BK, MW, BC), pp. 2838–2843.
ICPRICPR-2014-LaiSTH #3d #using
3-D Gaze Tracking Using Pupil Contour Features (CCL, SWS, HRT, YPH), pp. 1162–1166.
ICPRICPR-2014-LiewY #detection #feature model #novel #performance #robust
Generalized BRIEF: A Novel Fast Feature Extraction Method for Robust Hand Detection (CFL, TY), pp. 3014–3019.
ICPRICPR-2014-LiuL0L #classification #image #learning
Regularized Hierarchical Feature Learning with Non-negative Sparsity and Selectivity for Image Classification (BL, JL, XB, HL), pp. 4293–4298.
ICPRICPR-2014-LiuLS #documentation #image #novel
Novel Global and Local Features for Near-Duplicate Document Image Matching (LL, YL, CYS), pp. 4624–4629.
ICPRICPR-2014-MatsukawaOS #identification
Person Re-identification via Discriminative Accumulation of Local Features (TM, TO, YS), pp. 3975–3980.
ICPRICPR-2014-MatveevG #approximate #detection #segmentation
Iris Segmentation System Based on Approximate Feature Detection with Subsequent Refinements (IM, KG), pp. 1704–1709.
ICPRICPR-2014-McCarthyCO #classification #image
The Contribution of Morphological Features in the Classification of Prostate Carcinoma in Digital Pathology Images (NM, PC, GO), pp. 3269–3273.
ICPRICPR-2014-MehriMHGMM #benchmark #documentation #evaluation #metric #performance #set
Performance Evaluation and Benchmarking of Six Texture-Based Feature Sets for Segmenting Historical Documents (MM, MM, PH, PGK, MAM, RM), pp. 2885–2890.
ICPRICPR-2014-MekonnenLHB #detection #optimisation #people
People Detection with Heterogeneous Features and Explicit Optimization on Computation Time (AAM, FL, AH, CB), pp. 4322–4327.
ICPRICPR-2014-MoilanenZP #agile #analysis #difference #using
Spotting Rapid Facial Movements from Videos Using Appearance-Based Feature Difference Analysis (AM, GZ, MP), pp. 1722–1727.
ICPRICPR-2014-NeumannHKKB #classification #image
Erosion Band Features for Cell Phone Image Based Plant Disease Classification (MN, LH, BK, KK, CB), pp. 3315–3320.
ICPRICPR-2014-NieJ #learning #linear #using
Feature Learning Using Bayesian Linear Regression Model (SN, QJ), pp. 1502–1507.
ICPRICPR-2014-NieKZ #learning #recognition #using
Periocular Recognition Using Unsupervised Convolutional RBM Feature Learning (LN, AK, SZ), pp. 399–404.
ICPRICPR-2014-OhyamaYWK #recognition #using
Improving Accuracy of Printed Character Recognition Using Hexagonal Zoning of Directional Histogram Feature (WO, AY, TW, FK), pp. 2697–2702.
ICPRICPR-2014-OuyangYLW #performance #robust
A FAST Extreme Illumination Robust Feature in Affine Space (PO, SY, LL, SW), pp. 2365–2370.
ICPRICPR-2014-OuyedA #classification #kernel
Feature Relevance for Kernel Logistic Regression and Application to Action Classification (OO, MSA), pp. 1325–1329.
ICPRICPR-2014-PedagadiOB #detection
Integral Line Scan Features for Pedestrian Detection (SP, JO, BAB), pp. 2383–2388.
ICPRICPR-2014-PengWQP #encoding #evaluation #learning #recognition #taxonomy
A Joint Evaluation of Dictionary Learning and Feature Encoding for Action Recognition (XP, LW, YQ, QP), pp. 2607–2612.
ICPRICPR-2014-QureshiHA #probability #using
A Probabilistic Model for the Optimal Configuration of Retinal Junctions Using Theoretically Proven Features (TAQ, AH, BAD), pp. 3304–3309.
ICPRICPR-2014-RenL #gender #recognition #using
Gender Recognition Using Complexity-Aware Local Features (HR, ZNL), pp. 2389–2394.
ICPRICPR-2014-RenYZH #classification #image #learning #nearest neighbour
Learning Convolutional Nonlinear Features for K Nearest Neighbor Image Classification (WR, YY, JZ, KH), pp. 4358–4363.
ICPRICPR-2014-ReschLL #image
Local Image Feature Matching Improvements for Omnidirectional Camera Systems (BR, JL, HPAL), pp. 918–923.
ICPRICPR-2014-RodriguesPPW #approach #feature model
A Binary Krill Herd Approach for Feature Selection (DR, LAMP, JPP, SATW), pp. 1407–1412.
ICPRICPR-2014-SatoKSK #classification #learning #multi
Learning Multiple Complex Features Based on Classification Results (YS, KK, YS, MK), pp. 3369–3373.
ICPRICPR-2014-ShivakumaraSPBT #identification #video
Gradient-Angular-Features for Word-wise Video Script Identification (PS, NS, UP, MB, CLT), pp. 3098–3103.
ICPRICPR-2014-ShivramRG #case study #comparative #identification #modelling #online
Data Sufficiency for Online Writer Identification: A Comparative Study of Writer-Style Space vs. Feature Space Models (AS, CR, VG), pp. 3121–3125.
ICPRICPR-2014-SicreJ #classification #image
Discovering and Aligning Discriminative Mid-level Features for Image Classification (RS, FJ), pp. 1975–1980.
ICPRICPR-2014-SjolundJAKN #segmentation
Skull Segmentation in MRI by a Support Vector Machine Combining Local and Global Features (JS, AEJ, MTA, HK, HN), pp. 3274–3279.
ICPRICPR-2014-SongLZC #adaptation #performance #using
Scale Adaptive Tracking Using Mean Shift and Efficient Feature Matching (YS, SL, JZ, HC), pp. 2233–2238.
ICPRICPR-2014-SouzaSB #classification
Extracting Texture Features for Time Series Classification (VMAdS, DFS, GEAPAB), pp. 1425–1430.
ICPRICPR-2014-SunZL #adaptation #detection
An Adaptive-Profile Active Shape Model for Facial-Feature Detection (KS, HZ, KML), pp. 2849–2854.
ICPRICPR-2014-TerissiPG #classification #random #using
Lip Reading Using Wavelet-Based Features and Random Forests Classification (LDT, MP, JCG), pp. 791–796.
ICPRICPR-2014-TouaziMB #feature model #game studies
Feature Selection Scheme Based on Zero-Sum Two-Player Game (AT, FM, DB), pp. 1342–1347.
ICPRICPR-2014-TsukiokaK
Selection of Features in Accord with Population Drift (HT, MK), pp. 1591–1596.
ICPRICPR-2014-UbukataSTMKMU #detection #image #performance #segmentation
Fast Human Detection Combining Range Image Segmentation and Local Feature Based Detection (TU, MS, KT, AM, TK, GM, KU), pp. 4281–4286.
ICPRICPR-2014-WangGLYWY #analysis #canonical #correlation
Unsupervised Discriminant Canonical Correlation Analysis for Feature Fusion (SW, XG, JL, JYY, RW, JY), pp. 1550–1555.
ICPRICPR-2014-WangLSSC #detection #evaluation
Evaluation of Feature Detectors and Descriptors for Motion Detection from Aerial Videos (CW, SL, YS, YS, HC), pp. 2596–2601.
ICPRICPR-2014-WangSWB #consistency
Label Consistent Fisher Vectors for Supervised Feature Aggregation (QW, XS, MW, KLB), pp. 3588–3593.
ICPRICPR-2014-WenLWCW #classification #feature model #robust
Optimal Feature Selection for Robust Classification via l2, 1-Norms Regularization (JW, ZL, WKW, JC, MW), pp. 517–521.
ICPRICPR-2014-WenZLDC #3d #multi #retrieval #sketching
Sketch-Based 3D Model Retrieval via Multi-feature Fusion (YW, CZ, JL, SD, SC), pp. 4570–4575.
ICPRICPR-2014-WuJ #detection #learning
Learning the Deep Features for Eye Detection in Uncontrolled Conditions (YW, QJ), pp. 455–459.
ICPRICPR-2014-XiaoHL #3d #estimation #re-engineering
3D Face Reconstruction via Feature Point Depth Estimation and Shape Deformation (QX, LH, PL), pp. 2257–2262.
ICPRICPR-2014-YangD #identification #novel #using
Novel HHT-Based Features for Biometric Identification Using EEG Signals (SY, FD), pp. 1922–1927.
ICPRICPR-2014-YanJY #feature model #representation
Sparse Representation Preserving for Unsupervised Feature Selection (HY, ZJ, JY), pp. 1574–1578.
ICPRICPR-2014-ZambaniniKK #consistency #evaluation #geometry
Classifying Ancient Coins by Local Feature Matching and Pairwise Geometric Consistency Evaluation (SZ, AK, MK), pp. 3032–3037.
ICPRICPR-2014-ZhangHLHZL #approach #feature model #hybrid
A Hybrid Feature Selection Approach by Correlation-Based Filters and SVM-RFE (JZ, XH, PPL, WH, YZ, HL), pp. 3684–3689.
ICPRICPR-2014-ZhangHWZ #multi #parsing
Enhanced Human Parsing with Multiple Feature Fusion and Augmented Pose Model (ZZ, JH, YW, YZ), pp. 369–374.
ICPRICPR-2014-ZhangKBC #detection
Center-Surround Contrast Features for Pedestrian Detection (SZ, DAK, CB, ABC), pp. 2293–2298.
ICPRICPR-2014-ZhangLYQWTZ #detection #statistics
Sufficient Statistics Feature Mapping over Deep Boltzmann Machine for Detection (CZ, XL, JY, SQ, YW, CT, YZ), pp. 827–832.
ICPRICPR-2014-Zhao
Euclidean Structure from Conic Feature Correspondences (ZZ), pp. 4010–4014.
ICPRICPR-2014-ZhenS #evaluation #performance #recognition
A Performance Evaluation on Action Recognition with Local Features (XZ, LS), pp. 4495–4500.
ICPRICPR-2014-ZhouIWBPKO #learning #performance
Transfer Learning of a Temporal Bone Performance Model via Anatomical Feature Registration (YZ, II, SNRW, JB, PP, GK, SO), pp. 1916–1921.
ICPRICPR-2014-ZhouZYL #feature model #polynomial #recognition
Improving Handwritten Chinese Character Recognition with Discriminative Quadratic Feature Extraction (MKZ, XYZ, FY, CLL), pp. 244–249.
ICPRICPR-2014-ZhuWYJ #learning #modelling #multi #recognition #semantics
Multiple-Facial Action Unit Recognition by Shared Feature Learning and Semantic Relation Modeling (YZ, SW, LY, QJ), pp. 1663–1668.
KDDKDD-2014-GongZFY #learning #multi #performance
Efficient multi-task feature learning with calibration (PG, JZ, WF, JY), pp. 761–770.
KDDKDD-2014-NguyenCRB #effectiveness #feature model
Effective global approaches for mutual information based feature selection (XVN, JC, SR, JB), pp. 512–521.
KDDKDD-2014-PurushothamMKO #feature model #higher-order #interactive #learning #modelling
Factorized sparse learning models with interpretable high order feature interactions (SP, MRM, CCJK, RO), pp. 552–561.
KDDKDD-2014-XiangYY
Simultaneous feature and feature group selection through hard thresholding (SX, TY, JY), pp. 532–541.
KDDKDD-2014-XuHWZ #feature model
Gradient boosted feature selection (ZEX, GH, KQW, AXZ), pp. 522–531.
KDIRKDIR-2014-NagwanshiM #detection #semantics #sentiment #using
Sarcasm Detection using Sentiment and Semantic Features (PN, CEVM), pp. 418–424.
KMISKMIS-2014-Schmitt #approach #generative #information management #novel
Proposing a Next Generation of Knowledge Management Systems for Creative Collaborations in Support of Individuals and Institutions — Featuring a Novel Approach for Meme-based Personal Knowledge Management (US), pp. 346–353.
SEKESEKE-2014-Al-MsiedeenSHUV #implementation #object-oriented #source code
Documenting the Mined Feature Implementations from the Object-oriented Source Code of a Collection of Software Product Variants (RAM, AS, MH, CU, SV), pp. 138–143.
SEKESEKE-2014-GaoKN #estimation #learning #quality #ranking
Comparing Two Approaches for Adding Feature Ranking to Sampled Ensemble Learning for Software Quality Estimation (KG, TMK, AN), pp. 280–285.
SEKESEKE-2014-LianZ #feature model #product line
An Evolutionary Methodology for Optimized Feature Selection in Software Product Lines (XL, LZ), pp. 63–66.
SEKESEKE-2014-MaazounBB #feature model
Feature model recovery from product variants based on a cloning technique (JM, NB, HBA), pp. 431–436.
SEKESEKE-2014-SalmanSD #clustering #feature model #information retrieval
Feature Location in a Collection of Product Variants: Combining Information Retrieval and Hierarchical Clustering (HES, AS, CD), pp. 426–430.
SEKESEKE-2014-SalmanSD14a #concept analysis #impact analysis #using
Feature-Level Change Impact Analysis Using Formal Concept Analysis (HES, AS, CD), pp. 447–452.
SIGIRSIGIR-2014-DaltonDA #knowledge base #query #using
Entity query feature expansion using knowledge base links (JD, LD, JA), pp. 365–374.
SIGIRSIGIR-2014-Sebastian #clustering #predict #semantics #using
Cluster links prediction for literature based discovery using latent structure and semantic features (YS), p. 1275.
MODELSMoDELS-2014-BergerNRACW #industrial #modelling #variability
Three Cases of Feature-Based Variability Modeling in Industry (TB, DN, RR, JMA, KC, AW), pp. 302–319.
MODELSMoDELS-2014-Reinhartz-BergerFH #feature model #modelling
Comprehending Feature Models Expressed in CVL (IRB, KF, ØH), pp. 501–517.
MODELSMoDELS-2014-BergerNRACW #industrial #modelling #variability
Three Cases of Feature-Based Variability Modeling in Industry (TB, DN, RR, JMA, KC, AW), pp. 302–319.
MODELSMoDELS-2014-Reinhartz-BergerFH #feature model #modelling
Comprehending Feature Models Expressed in CVL (IRB, KF, ØH), pp. 501–517.
PLATEAUPLATEAU-2014-RoulyOS #bibliography #ide #usability #visual notation
Usability and Suitability Survey of Features in Visual Ides for Non-Programmers (JMR, JDO, ES), pp. 31–42.
GPCEGPCE-2014-RuprechtHL #automation #feature model #product line #scalability
Automatic feature selection in large-scale system-software product lines (AR, BH, DL), pp. 39–48.
RERE-2014-BruunHIJK #distributed #mobile #requirements
Handling design-level requirements across distributed teams: Developing a new feature for 12 Danish mobile banking apps (LB, MBH, JBI, JBJ, BK), pp. 335–343.
RERE-2014-GuzmanM #analysis #fine-grained #how #sentiment
How Do Users Like This Feature? A Fine Grained Sentiment Analysis of App Reviews (EG, WM), pp. 153–162.
RERE-2014-LiuSYM14a #feature model #reasoning #requirements
Combined goal and feature model reasoning with the User Requirements Notation and jUCMNav (YL, YS, XY, GM), pp. 321–322.
RERE-2014-SlavinLNB #diagrams #feature model #requirements #security #using
Managing security requirements patterns using feature diagram hierarchies (RS, JML, JN, TDB), pp. 193–202.
RERE-2014-TranM #approach #evolution #feature model #nondeterminism
An Approach for Decision Support on the Uncertainty in Feature Model Evolution (LMST, FM), pp. 93–102.
RERE-2014-ZhouLLLKL #feature model #requirements #towards #validation
Towards feature-oriented requirements validation for automotive systems (JZ, YL, KL, HL, DK, BL), pp. 428–436.
SACSAC-2014-AmadiniGM #constraints #theorem proving
An enhanced features extractor for a portfolio of constraint solvers (RA, MG, JM), pp. 1357–1359.
SACSAC-2014-AminikhanghahiWSSJ #effectiveness #feature model #smarttech
Effective tumor feature extraction for smart phone based microwave tomography breast cancer screening (SA, WW, SYS, SHS, SIJ), pp. 674–679.
SACSAC-2014-BeoharM #consistency #testing
Input-output conformance testing based on featured transition systems (HB, MRM), pp. 1272–1278.
SACSAC-2014-BergamascoN #3d #approach #feature model #retrieval #using
A new local feature extraction approach for content-based 3D medical model retrieval using shape descriptor (LCCB, FLSN), pp. 902–907.
SACSAC-2014-FerrazPG #feature model #symmetry
Feature description based on center-symmetric local mapped patterns (CTF, OPJ, AG), pp. 39–44.
SACSAC-2014-JunAK #detection #using
DDoS attack detection by using packet sampling and flow features (JHJ, CWA, SHK), pp. 711–712.
SACSAC-2014-RolimBCCAPM #approach #multimodal #recommendation
A recommendation approach for digital TV systems based on multimodal features (RR, FB, AC, GC, HOdA, AP, AFM), pp. 289–291.
SACSAC-2014-SypeS #case study #online #requirements #social
Case study: legal requirements for the use of social login features for online reputation updates (YSVDS, JMS), pp. 1698–1705.
SACSAC-2014-YoonKHKRC #metric #reachability #similarity
Reachability vectors: features for link-based similarity measures (SHY, JSK, JH, SWK, MR, HJC), pp. 594–597.
SACSAC-2014-Zanchettin #recognition
Face recognition based on global and local features (CZ), pp. 55–57.
FSEFSE-2014-Behringer #implementation
Integrating approaches for feature implementation (BB), pp. 775–778.
FSEFSE-2014-BocovichA #feature model #interactive
Variable-specific resolutions for feature interactions (CB, JMA), pp. 553–563.
ICSEICSE-2014-RibeiroBK #interface #maintenance
Feature maintenance with emergent interfaces (MR, PB, CK), pp. 989–1000.
SLESLE-2014-JaksicFCG #feature model #modelling #usability #visual notation
Evaluating the Usability of a Visual Feature Modeling Notation (AJ, RBF, PC, SG), pp. 122–140.
SPLCSPLC-2014-BeucheS #feature model #modelling #variability
Managing variability with feature models (DB, MS), p. 364.
SPLCSPLC-2014-MennickeLSW #automation #feature model #petri net #process #verification #workflow
Automated verification of feature model configuration processes based on workflow Petri nets (SM, ML, JS, TW), pp. 62–71.
SPLCSPLC-2014-MoensT #development #multitenancy
Feature-based application development and management of multi-tenant applications in clouds (HM, FDT), pp. 72–81.
SPLCSPLC-2014-QuintonPBDB #consistency #evolution #feature model #modelling
Consistency checking for the evolution of cardinality-based feature models (CQ, AP, DLB, LD, GB), pp. 122–131.
SPLCSPLC-2014-SchroterSTS #interface #product line #programming
Feature-context interfaces: tailored programming interfaces for software product lines (RS, NS, TT, GS), pp. 102–111.
SPLCSPLC-2014-ShakerA #behaviour #interactive #product line
Behaviour interactions among product-line features (PS, JMA), pp. 242–246.
SPLCSPLC-2014-SteinNC #feature model #multi
Preference-based feature model configuration with multiple stakeholders (JS, IN, EC), pp. 132–141.
SPLCSPLC-2014-YuZZJ #automation #case study #feature model #named
TDL: a transformation description language from feature model to use case for automated use case derivation (WY, WZ, HZ, ZJ), pp. 187–196.
ICSTICST-2014-ZaeemPK #automation #generative #mobile #testing
Automated Generation of Oracles for Testing User-Interaction Features of Mobile Apps (RNZ, MRP, SK), pp. 183–192.
ISSTAISSTA-2014-ChoudharyPO #web
Cross-platform feature matching for web applications (SRC, MRP, AO), pp. 82–92.
ASEASE-2013-ChandramohanTBSP #approach #behaviour #bound #detection #modelling #scalability
A scalable approach for malware detection through bounded feature space behavior modeling (MC, HBKT, LCB, LKS, BMP), pp. 312–322.
ASEASE-2013-PohlSP #complexity #feature model #modelling
Measuring the structural complexity of feature models (RP, VS, KP), pp. 454–464.
ASEASE-2013-ThungWLL #api #automation #feature model #recommendation
Automatic recommendation of API methods from feature requests (FT, SW, DL, JLL), pp. 290–300.
CASECASE-2013-LuSXPO #automation #graph #multi #using
Automatic building exterior mapping using multilayer feature graphs (YL, DS, YX, AGAP, SO), pp. 162–167.
DACDAC-2013-YuLJC #classification #detection #feature model #using
Machine-learning-based hotspot detection using topological classification and critical feature extraction (YTY, GHL, IHRJ, CC), p. 6.
DocEngDocEng-2013-NourashrafeddinMA #clustering #documentation #interactive #using
Interactive text document clustering using feature labeling (SN, EEM, DVA), pp. 61–70.
DRRDRR-2013-ShiXJX #integration
Character feature integration of Chinese calligraphy and font (CS, JX, WJ, CX).
ICDARICDAR-2013-AhmedSLD #segmentation #using
A Generic Method for Stamp Segmentation Using Part-Based Features (SA, FS, ML, AD), pp. 708–712.
ICDARICDAR-2013-AlaeiDG #detection #probability #representation #using
Logo Detection Using Painting Based Representation and Probability Features (AA, MD, NG), pp. 1235–1239.
ICDARICDAR-2013-AlvaroSB #classification #hybrid #network #online
Classification of On-Line Mathematical Symbols with Hybrid Features and Recurrent Neural Networks (FA, JAS, JMB), pp. 1012–1016.
ICDARICDAR-2013-AmaralFB #feature model #forensics #identification
Feature Selection for Forensic Handwriting Identification (AMMMA, COdAF, FB), pp. 922–926.
ICDARICDAR-2013-BertrandGTFO #detection #documentation
A System Based on Intrinsic Features for Fraudulent Document Detection (RB, PGK, ORT, PF, JMO), pp. 106–110.
ICDARICDAR-2013-BlucheNK #feature model #network #recognition #word
Feature Extraction with Convolutional Neural Networks for Handwritten Word Recognition (TB, HN, CK), pp. 285–289.
ICDARICDAR-2013-ChengSAT #classification #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-ChherawalaRC #automation #design #question #recognition
Feature Design for Offline Arabic Handwriting Recognition: Handcrafted vs Automated? (YC, PPR, MC), pp. 290–294.
ICDARICDAR-2013-DanielsB #identification
Discriminating Features for Writer Identification (ZAD, HSB), pp. 1385–1389.
ICDARICDAR-2013-GebhardtGSD #authentication #detection #documentation #using
Document Authentication Using Printing Technique Features and Unsupervised Anomaly Detection (JG, MG, FS, AD), pp. 479–483.
ICDARICDAR-2013-HuC #classification #pseudo #using #verification
Offline Signature Verification Using Real Adaboost Classifier Combination of Pseudo-dynamic Features (JH, YC), pp. 1345–1349.
ICDARICDAR-2013-HuZ #multi #using
Segmenting Handwritten Math Symbols Using AdaBoost and Multi-scale Shape Context Features (LH, RZ), pp. 1180–1184.
ICDARICDAR-2013-NafchiMC #documentation #image
Application of Phase-Based Features and Denoising in Postprocessing and Binarization of Historical Document Images (HZN, RFM, MC), pp. 220–224.
ICDARICDAR-2013-PhamDBR #consistency #geometry #locality #performance #robust
Robust Symbol Localization Based on Junction Features and Efficient Geometry Consistency Checking (TAP, MD, SB, JYR), pp. 1083–1087.
ICDARICDAR-2013-RothackerRF #documentation #word
Bag-of-Features HMMs for Segmentation-Free Word Spotting in Handwritten Documents (LR, MR, GAF), pp. 1305–1309.
ICDARICDAR-2013-SantoshWL #retrieval
Relation Bag-of-Features for Symbol Retrieval (KCS, LW, BL), pp. 768–772.
ICDARICDAR-2013-Siriteerakul #classification
Mixed Thai-English Character Classification Based on Histogram of Oriented Gradient Feature (TS), pp. 847–851.
ICDARICDAR-2013-SuDPL13a #independence #novel #recognition #set
A Novel Baseline-independent Feature Set for Arabic Handwriting Recognition (BS, XD, LP, CL), pp. 1250–1254.
ICDARICDAR-2013-SunBOK #detection #using
Specific Comic Character Detection Using Local Feature Matching (WS, JCB, JMO, KK), pp. 275–279.
ICDARICDAR-2013-SurintaSW #comparison
A Comparison of Feature and Pixel-Based Methods for Recognizing Handwritten Bangla Digits (OS, LS, MW), pp. 165–169.
ICDARICDAR-2013-YiYT #case study #comparative #recognition
Feature Representations for Scene Text Character Recognition: A Comparative Study (CY, XY, YT), pp. 907–911.
ICDARICDAR-2013-YuEC #classification #online
Mental Workload Classification via Online Writing Features (KY, JE, FC), pp. 1110–1114.
ICDARICDAR-2013-ZhuZ #detection #image #recognition #using
Label Detection and Recognition for USPTO Images Using Convolutional K-Means Feature Quantization and Ada-Boost (SZ, RZ), pp. 633–637.
VLDBVLDB-2013-KondaKRS #data analysis #enterprise #feature model #using
Feature Selection in Enterprise Analytics: A Demonstration using an R-based Data Analytics System (PK, AK, CR, VS), pp. 1306–1309.
ITiCSEITiCSE-2013-RodgerGML
Increasing the experimentation of theoretical computer science with new features in JFLAP (SHR, JG, IM, PL), p. 351.
FASEFASE-2013-HaslingerLE #feature model #modelling #on the #set
On Extracting Feature Models from Sets of Valid Feature Combinations (ENH, RELH, AE), pp. 53–67.
CSMRCSMR-2013-KazatoHKOOMHS #feature model #identification #incremental #source code
Incremental Feature Location and Identification in Source Code (HK, SH, TK, TO, SO, SM, TH, MS), pp. 371–374.
CSMRCSMR-2013-NegaraTS #detection #web
Feature Detection in Ajax-Enabled Web Applications (NN, NT, ES), pp. 154–163.
ICPCICPC-2013-BassettK #feature model #retrieval
Structural information based term weighting in text retrieval for feature location (BB, NAK), pp. 133–141.
ICPCICPC-2013-KobayashiKYKM #architecture #visualisation
SArF map: Visualizing software architecture from feature and layer viewpoints (KK, MK, KY, KK, AM), pp. 43–52.
ICPCICPC-2013-ZhangH #api #problem
Extracting problematic API features from forum discussions (YZ, DH), pp. 142–151.
ICSMEICSM-2013-AlhindawiDCM #feature model #source code
Improving Feature Location by Enhancing Source Code with Stereotypes (NA, ND, MLC, JIM), pp. 300–309.
ICSMEICSM-2013-HillBBDLO #feature model #question
Which Feature Location Technique is Better? (EH, AB, DB, BD, DL, RO), pp. 408–411.
ICSMEICSM-2013-NovaisNGM #comprehension #evolution
SourceMiner Evolution: A Tool for Supporting Feature Evolution Comprehension (RLN, CN, AG, MGM), pp. 508–511.
ICSMEICSM-2013-SemenenkoDS #image #machine learning #named #testing
Browserbite: Accurate Cross-Browser Testing via Machine Learning over Image Features (NS, MD, TS), pp. 528–531.
ICSMEICSM-2013-SiebraMSS #framework
The Adventure of Developing a Software Application on a Pre-release Platform: Features and Learned Lessons (CdS, AM, FQBdS, ALMS), pp. 556–559.
MSRMSR-2013-IacobH #feature model #mobile #online
Retrieving and analyzing mobile apps feature requests from online reviews (CI, RH), pp. 41–44.
WCREWCRE-2013-IshioHKO #automation #effectiveness #feature model #on the
On the effectiveness of accuracy of automated feature location technique (TI, SH, HK, TO), pp. 381–390.
HCIDUXU-PMT-2013-Moallem #network
Location, Location, Location: About Home Networking Devices Location and Features (AM), pp. 107–114.
HCIDUXU-WM-2013-Igler #approach #design #evaluation #mobile #prototype
Feature Evaluation for Mobile Applications: A Design Science Approach Based on Evolutionary Software Prototypes (BI), pp. 673–681.
HCIHCI-III-2013-WangLLD #algorithm #performance #realtime #visual notation
A New Real-Time Visual SLAM Algorithm Based on the Improved FAST Features (LW, RL, CL, FD), pp. 206–215.
HCIHCI-IMT-2013-AlexandrisM #human-computer #multi
Linguistic Processing of Implied Information and Connotative Features in Multilingual HCI Applications (CA, IM), pp. 13–22.
HCIHCI-IMT-2013-ClamannMK #artificial reality #comparison #simulation #visual notation
Comparison of Enhanced Visual and Haptic Features in a Virtual Reality-Based Haptic Simulation (MPC, WM, DBK), pp. 551–560.
HCIHCI-IMT-2013-SakairiTKG #editing #multi #using #visual notation
Multi-layer Control and Graphical Feature Editing Using Server-Side Rendering on Ajax-GIS (TS, TT, KK, YG), pp. 722–729.
HCIHIMI-HSM-2013-HondaON #estimation
Estimation of the Facial Impression from Individual Facial Features for Constructing the Makeup Support System (AH, CO, KN), pp. 92–99.
ICEISICEIS-v2-2013-VianaDPP #framework #named
F3 — From Features to Framework (MCV, RSD, RADP, AFdP), pp. 110–117.
CIKMCIKM-2013-AyadiTDJH #correlation #image #modelling #query #retrieval #using
Correlating medical-dependent query features with image retrieval models using association rules (HA, MT, MD, MBJ, JXH), pp. 299–308.
CIKMCIKM-2013-FangZ #feature model #learning #multi
Discriminative feature selection for multi-view cross-domain learning (ZF, Z(Z), pp. 1321–1330.
CIKMCIKM-2013-GuoZ #classification #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-LiGLYS #framework #multimodal
A multimodal framework for unsupervised feature fusion (XL, JG, HL, LY, RKS), pp. 897–902.
CIKMCIKM-2013-QiuYJ #clustering #interactive #modelling
Modeling interaction features for debate side clustering (MQ, LY, JJ), pp. 873–878.
CIKMCIKM-2013-RothK #modelling #quality
Feature-based models for improving the quality of noisy training data for relation extraction (BR, DK), pp. 1181–1184.
CIKMCIKM-2013-TuLLHL #information retrieval #modelling #proximity #statistics
Exploiting proximity feature in statistical translation models for information retrieval (XT, JL, BL, TH, ML), pp. 1237–1240.
CIKMCIKM-2013-ZhouC #documentation
Entity-centric document filtering: boosting feature mapping through meta-features (MZ, KCCC), pp. 119–128.
ECIRECIR-2013-JeongM #classification #dependence #recognition #using
Using WordNet Hypernyms and Dependency Features for Phrasal-Level Event Recognition and Type Classification (YJ, SHM), pp. 267–278.
ECIRECIR-2013-OlteanuPLA #predict #web
Web Credibility: Features Exploration and Credibility Prediction (AO, SP, XL, KA), pp. 557–568.
ECIRECIR-2013-ZhangZBC #categorisation #distance #encoding #visual notation
Encoding Local Binary Descriptors by Bag-of-Features with Hamming Distance for Visual Object Categorization (YZ, CZ, SB, LC), pp. 630–641.
ICMLICML-c1-2013-0005LSL #feature model #learning #modelling #online
Online Feature Selection for Model-based Reinforcement Learning (TTN, ZL, TS, TYL), pp. 498–506.
ICMLICML-c1-2013-GongGS #adaptation #invariant #learning
Connecting the Dots with Landmarks: Discriminatively Learning Domain-Invariant Features for Unsupervised Domain Adaptation (BG, KG, FS), pp. 222–230.
ICMLICML-c1-2013-HeaukulaniG #modelling #network #probability #social
Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks (CH, ZG), pp. 275–283.
ICMLICML-c1-2013-KolarL #classification #feature model
Feature Selection in High-Dimensional Classification (MK, HL), pp. 329–337.
ICMLICML-c1-2013-MaatenCTW #learning
Learning with Marginalized Corrupted Features (LvdM, MC, ST, KQW), pp. 410–418.
ICMLICML-c1-2013-MuandetBS #invariant #representation
Domain Generalization via Invariant Feature Representation (KM, DB, BS), pp. 10–18.
ICMLICML-c1-2013-XiangTY #feature model #optimisation #performance
Efficient Sparse Group Feature Selection via Nonconvex Optimization (SX, XT, JY), pp. 284–292.
ICMLICML-c2-2013-Hui #modelling #visual notation
Direct Modeling of Complex Invariances for Visual Object Features (KYH), pp. 352–360.
ICMLICML-c2-2013-SohnZLL #learning
Learning and Selecting Features Jointly with Point-wise Gated Boltzmann Machines (KS, GZ, CL, HL), pp. 217–225.
ICMLICML-c3-2013-AppelFDP
Quickly Boosting Decision Trees — Pruning Underachieving Features Early (RA, TJF, PD, PP), pp. 594–602.
ICMLICML-c3-2013-JiaVD #on the
On Compact Codes for Spatially Pooled Features (YJ, OV, TD), pp. 549–557.
ICMLICML-c3-2013-MemisevicE #invariant #learning #problem
Learning invariant features by harnessing the aperture problem (RM, GE), pp. 100–108.
ICMLICML-c3-2013-SabatoK #multi
Feature Multi-Selection among Subjective Features (SS, AK), pp. 810–818.
ICMLICML-c3-2013-WangNH13a #clustering #learning #multi
Multi-View Clustering and Feature Learning via Structured Sparsity (HW, FN, HH), pp. 352–360.
KDDKDD-2013-PhamP #kernel #performance #polynomial #scalability
Fast and scalable polynomial kernels via explicit feature maps (NP, RP), pp. 239–247.
KDDKDD-2013-SunBK #identification #optimisation #polynomial
Quadratic optimization to identify highly heritable quantitative traits from complex phenotypic features (JS, JB, HRK), pp. 811–819.
KDDKDD-2013-WangS #classification #multi #relational #social #using
Multi-label relational neighbor classification using social context features (XW, GS), pp. 464–472.
KDDKDD-2013-ZhangWF #recommendation
Combining latent factor model with location features for event-based group recommendation (WZ, JW, WF), pp. 910–918.
KDDKDD-2013-ZhouLSYWY #identification #named
FeaFiner: biomarker identification from medical data through feature generalization and selection (JZ, ZL, JS, LY, FW, JY), pp. 1034–1042.
KDIRKDIR-KMIS-2013-CheetiSC #adaptation #approach #classification #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.
KDIRKDIR-KMIS-2013-CherichiF #microblog
Relevant Information Discovery in Microblogs — Combining Post’s Features and Author’s Features to Improve Search Results (SC, RF), pp. 128–135.
KDIRKDIR-KMIS-2013-GirdauskieneS #what
Assessing Environmental Dimensions for Creativity and Knowledge Creation — What Features of Task, Group and Time do make an Impact on Creativity and Knowledge Creation in a Creative Organization (LG, AS), pp. 532–538.
KDIRKDIR-KMIS-2013-MelnichenkoB #automation #image #low level #random
Automatic Image Annotation with Low-level Features and Conditional Random Fields (AM, AB), pp. 197–201.
KDIRKDIR-KMIS-2013-WaadBL #algorithm #feature model #rank #search-based
Feature Selection by Rank Aggregation and Genetic Algorithms (BW, ABB, ML), pp. 74–81.
MLDMMLDM-2013-MaziluCGRHT #detection #learning #predict
Feature Learning for Detection and Prediction of Freezing of Gait in Parkinson’s Disease (SM, AC, EG, DR, JMH, GT), pp. 144–158.
MLDMMLDM-2013-MinhAN #algorithm #feature model
DCA Based Algorithms for Feature Selection in Semi-supervised Support Vector Machines (LHM, LTHA, MCN), pp. 528–542.
MLDMMLDM-2013-StambaughYB #feature model
Analytic Feature Selection for Support Vector Machines (CS, HY, FB), pp. 219–233.
MLDMMLDM-2013-VavreckaL #classification #feature model
EEG Feature Selection Based on Time Series Classification (MV, LL), pp. 520–527.
RecSysRecSys-2013-AharonABLABLRS #named #online #persistent #recommendation #set
OFF-set: one-pass factorization of feature sets for online recommendation in persistent cold start settings (MA, NA, EB, RL, RA, TB, LL, RR, OS), pp. 375–378.
RecSysRecSys-2013-KoenigsteinP #embedded #feature model #matrix #recommendation
Xbox movies recommendations: variational bayes matrix factorization with embedded feature selection (NK, UP), pp. 129–136.
RecSysRecSys-2013-RonenKZN #collaboration #recommendation
Selecting content-based features for collaborative filtering recommenders (RR, NK, EZ, NN), pp. 407–410.
RecSysRecSys-2013-TiroshiBKCK #network #predict #social
Cross social networks interests predictions based ongraph features (AT, SB, MAK, TC, TK), pp. 319–322.
SEKESEKE-2013-Al-MsiedeenSHUVS #concept analysis #mining #object-oriented #semantics #source code #using
Mining Features from the Object-Oriented Source Code of a Collection of Software Variants Using Formal Concept Analysis and Latent Semantic Indexing (RAM, ADS, MH, CU, SV, HES), pp. 244–249.
SEKESEKE-2013-FerreiraVQ #approach #product line #testing
A Mutation Approach to Feature Testing of Software Product Lines (JMF, SRV, MAQ), pp. 232–237.
SEKESEKE-2013-LosadaJ #documentation #identification #semantics
Processing rhetorical, morphosyntactic, and semantic features from corporate technical documents for identifying organizational domain knowledge (S) (BML, CMZJ), pp. 268–272.
SEKESEKE-2013-PossompesDHT #feature model #generative #modelling
Model-Driven Generation of Context-Specific Feature Models (TP, CD, MH, CT), pp. 250–255.
SEKESEKE-2013-RajasekharanMN #crowdsourcing #effectiveness #online
Effective Crowdsourcing for Software Feature Ideation in Online Co-Creation Forums (KR, APM, SKN), pp. 119–124.
SEKESEKE-2013-WangKWN #case study #feature model #first-order #metric #statistics
A Study on First Order Statistics-Based Feature Selection Techniques on Software Metric Data (HW, TMK, RW, AN), pp. 467–472.
SEKESEKE-2013-YuWYLY #evaluation #named #repository
HESA: The Construction and Evaluation of Hierarchical Software Feature Repository (YY, HW, GY, XL, CY), pp. 624–631.
SIGIRSIGIR-2013-ChandarWC #documentation #predict
Document features predicting assessor disagreement (PC, WW, BC), pp. 745–748.
SIGIRSIGIR-2013-MoshfeghiJ #behaviour #effectiveness #feedback #using
An effective implicit relevance feedback technique using affective, physiological and behavioural features (YM, JMJ), pp. 133–142.
MODELSMoDELS-2013-SemerathHV #constraints #domain-specific language #graph #query #validation
Validation of Derived Features and Well-Formedness Constraints in DSLs — By Mapping Graph Queries to an SMT-Solver (OS, ÁH, DV), pp. 538–554.
MODELSMoDELS-2013-WangGAL #automation #case study #feature model #industrial #testing #using
Automated Test Case Selection Using Feature Model: An Industrial Case Study (SW, AG, SA, ML), pp. 237–253.
MODELSMoDELS-2013-SemerathHV #constraints #domain-specific language #graph #query #validation
Validation of Derived Features and Well-Formedness Constraints in DSLs — By Mapping Graph Queries to an SMT-Solver (OS, ÁH, DV), pp. 538–554.
MODELSMoDELS-2013-WangGAL #automation #case study #feature model #industrial #testing #using
Automated Test Case Selection Using Feature Model: An Industrial Case Study (SW, AG, SA, ML), pp. 237–253.
ECOOPECOOP-2013-OliveiraSLC #algebra #feature model #programming
Feature-Oriented Programming with Object Algebras (BCdSO, TvdS, AL, WRC), pp. 27–51.
GPCEGPCE-2013-KolesnikovRHA #comparison #type checking
A comparison of product-based, feature-based, and family-based type checking (SSK, AvR, CH, SA), pp. 115–124.
RERE-2013-DietrichA #interface #requirements
A mode-based pattern for feature requirements, and a generic feature interface (DD, JMA), pp. 82–91.
RERE-2013-VogelsanagF #challenge #dependence #empirical #requirements #why
Why feature dependencies challenge the requirements engineering of automotive systems: An empirical study (AV, SF), pp. 267–272.
SACSAC-PL-J-2011-AcherCLF13 #domain-specific language #feature model #modelling #named #scalability
FAMILIAR: A domain-specific language for large scale management of feature models (MA, PC, PL, RBF), pp. 657–681.
SACSAC-2013-AraujoGMSAB #approach #composition #feature model #modelling
Advanced modularity for building SPL feature models: a model-driven approach (JA, MG, AMDM, IS, VA, ELAB), pp. 1246–1253.
SACSAC-2013-BarreirosM #constraints #feature model #modelling
Configuration support for feature models with soft constraints (JB, AMDM), pp. 1307–1308.
SACSAC-2013-CavalinKMO #framework #multi #recognition
A multiple feature vector framework for forest species recognition (PRC, MNK, JM, LESdO), pp. 16–20.
SACSAC-2013-DamakPBC #effectiveness #microblog #state of the art
Effectiveness of state-of-the-art features for microblog search (FD, KPS, MB, GC), pp. 914–919.
SACSAC-2013-HayashiIN #recommendation #visual notation
A visual analytics tool for system logs adopting variable recommendation and feature-based filtering (AH, TI, SN), pp. 996–998.
SACSAC-2013-HerzogKHFK #automation #identification #web
Feature-based object identification for web automation (CH, IK, WH, RRF, BKS), pp. 742–749.
SACSAC-2013-Jean-BaptisteMJA #adaptation #feature model #modelling #using
Modeling dynamic adaptations using augmented feature models (JBL, MTS, JMG, AB), pp. 1734–1741.
SACSAC-2013-Savoy #feature model
Feature selections for authorship attribution (JS), pp. 939–941.
ESEC-FSEESEC-FSE-2013-DavrilDHACH #feature model #scalability
Feature model extraction from large collections of informal product descriptions (JMD, ED, NH, MA, JCH, PH), pp. 290–300.
ESEC-FSEESEC-FSE-2013-LoharAZC #composition #data-driven
Improving trace accuracy through data-driven configuration and composition of tracing features (SL, SA, AZ, JCH), pp. 378–388.
ICSEICSE-2013-CordySHL #model checking #multi #product line
Beyond boolean product-line model checking: dealing with feature attributes and multi-features (MC, PYS, PH, AL), pp. 472–481.
ICSEICSE-2013-HenardPPKT #automation #feature model #modelling #testing #towards
Towards automated testing and fixing of re-engineered feature models (CH, MP, GP, JK, YLT), pp. 1245–1248.
ICSEICSE-2013-HerzigJZ #classification #debugging #how #predict
It’s not a bug, it’s a feature: how misclassification impacts bug prediction (KH, SJ, AZ), pp. 392–401.
ICSEICSE-2013-ScharfA #diagrams #editing #injection #sketching
Dynamic injection of sketching features into GEF based diagram editors (AS, TA), pp. 822–831.
ICSEICSE-2013-WangPXZ #feature model #interactive #multi
Improving feature location practice with multi-faceted interactive exploration (JW, XP, ZX, WZ), pp. 762–771.
ICSEICSE-2013-XingXJ #benchmark #feature model #kernel #metric #research #scalability
A large scale Linux-kernel based benchmark for feature location research (ZX, YX, SJ), pp. 1311–1314.
PLEASEPLEASE-2013-HuangYKHU #analysis #domain-specific language #mining #repository #towards
Domain analysis for mining software repositories: Towards feature-based DSL construction (CH, KY, YK, KH, NU), pp. 41–44.
PLEASEPLEASE-2013-PatelGS #feature model #interactive #testing #variability
Feature interaction testing of variability intensive systems (SP, PG, VS), pp. 53–56.
SPLCSPLC-2013-LinsbauerLE #traceability
Recovering traceability between features and code in product variants (LL, RELH, AE), pp. 131–140.
SPLCSPLC-2013-MuthigS #framework #product line
A framework for role-based feature management in software product line organizations (DM, JS), pp. 178–187.
SPLCSPLC-2013-Quinton0D #approach #constraints #feature model #modelling
Cardinality-based feature models with constraints: a pragmatic approach (CQ, DR, LD), pp. 162–166.
ISSTAISSTA-2013-HillsKV #empirical #perspective #php #static analysis
An empirical study of PHP feature usage: a static analysis perspective (MH, PK, JJV), pp. 325–335.
ISSTAISSTA-2013-Thum #contract #feature model #product line #verification
Product-line verification with feature-oriented contracts (TT), pp. 374–377.
RTARTA-2013-AvanziniM13a #complexity
Tyrolean Complexity Tool: Features and Usage (MA, GM), pp. 71–80.
ASEASE-2012-RubinC #difference #set #using
Locating distinguishing features using diff sets (JR, MC), pp. 242–245.
CASECASE-2012-Chang #detection #fault #feature model #process #using
Fault detection for plasma-enhanced chemical vapor deposition process using feature extraction (YJC), pp. 491–496.
CASECASE-2012-ParkM #behaviour #bound #clustering #hybrid #linear #performance #tool support
Performance bounds for hybrid flow lines: Fundamental behavior, practical features and application to linear cluster tools (KP, JRM), pp. 371–376.
CASECASE-2012-WeiM #design #framework #order #process #scheduling
Design of an order acceptance and scheduling module in a unified framework with product and process features (JW, YSM), pp. 968–973.
DACDAC-2012-MalburgFF #automation #design #hardware #locality #metric #using
Automated feature localization for hardware designs using coverage metrics (JM, AF, GF), pp. 941–946.
DocEngDocEng-2012-PenadesGC #documentation #feature model #modelling #workflow
Deriving document workflows from feature models (MdCP, AG, JHC), pp. 237–240.
DRRDRR-2012-Obafemi-AjayiAX #classification #documentation
Ensemble methods with simple features for document zone classification (TOA, GA, BX).
VLDBVLDB-2012-CandanRSW #constraints #named #using
sDTW: Computing DTW Distances using Locally Relevant Constraints based on Salient Feature Alignments (KSC, RR, MLS, XW), pp. 1519–1530.
VLDBVLDB-2012-TauheedHSMA #named #query
SCOUT: Prefetching for Latent Feature Following Queries (FT, TH, FS, HM, AA), pp. 1531–1542.
FASEFASE-2012-ThumSKAS #contract #design #feature model #programming
Applying Design by Contract to Feature-Oriented Programming (TT, IS, MK, SA, GS), pp. 255–269.
CSMRCSMR-2012-KazatoHOMHS #concept analysis #feature model #multi
Feature Location for Multi-Layer System Based on Formal Concept Analysis (HK, SH, SO, SM, TH, MS), pp. 429–434.
CSMRCSMR-2012-OlszakJ #composition #concept #how #legacy #question
Modularization of Legacy Features by Relocation and Reconceptualization: How Much is Enough? (AO, BNJ), pp. 171–180.
CSMRCSMR-2012-ZiadiFSZ #identification #source code
Feature Identification from the Source Code of Product Variants (TZ, LF, MAAdS, MZ), pp. 417–422.
ICPCICPC-2012-DitMP #feature model
A TraceLab-based solution for creating, conducting, and sharing feature location experiments (BD, EM, DP), pp. 203–208.
ICPCICPC-2012-KazatoHOMHS #feature model #towards
Toward structured location of features (HK, SH, SO, SM, TH, MS), pp. 255–256.
ICSMEICSM-2012-KobayashiKKYM #clustering #composition #dependence #using
Feature-gathering dependency-based software clustering using Dedication and Modularity (KK, MK, KK, KY, AM), pp. 462–471.
WCREWCRE-2012-MisraAKST #clustering #semantics
Software Clustering: Unifying Syntactic and Semantic Features (JM, KMA, VSK, SS, GT), pp. 113–122.
WCREWCRE-2012-XueXJ #feature model
Feature Location in a Collection of Product Variants (YX, ZX, SJ), pp. 145–154.
WCREWCRE-2012-ZiftciK #data mining #feature model #mining #using
Feature Location Using Data Mining on Existing Test-Cases (CZ, IK), pp. 155–164.
SEFMSEFM-2012-ZhangKJ #composition #verification
Verification of Aspectual Composition in Feature-Modeling (QZ, RK, JJ), pp. 109–125.
CAiSECAiSE-2012-AcherHCQLM #difference #feature model
Feature Model Differences (MA, PH, PC, CQ, PL, PM), pp. 629–645.
CAiSECAiSE-2012-EnsanBG #feature model #generative #modelling #product line #search-based #testing
Evolutionary Search-Based Test Generation for Software Product Line Feature Models (FE, EB, DG), pp. 613–628.
CAiSECAiSE-2012-KaragiannisMM #approach #evaluation #heatmap #metamodelling
Compliance Evaluation Featuring Heat Maps (CE-HM): A Meta-Modeling-Based Approach (DK, CM, AM), pp. 414–428.
CAiSECAiSE-2012-SchalerLRS #database #information management #using
Building Information System Variants with Tailored Database Schemas Using Features (MS, TL, MR, GS), pp. 597–612.
ICEISICEIS-v1-2012-LouatiBDS #behaviour #database #modelling #realtime
Modeling Structural, Temporal and Behavioral Features of a Real-Time Database (NL, RB, CD, BS), pp. 119–125.
CIKMCIKM-2012-AhmedADSA #behaviour #feature model #multi
Web-scale multi-task feature selection for behavioral targeting (AA, MA, AD, AJS, TA), pp. 1737–1741.
CIKMCIKM-2012-CamposBDC #feature model #identification
Time feature selection for identifying active household members (PGC, AB, FD, IC), pp. 2311–2314.
CIKMCIKM-2012-CandanRSW #named #scalability #set #visualisation
STFMap: query- and feature-driven visualization of large time series data sets (KSC, RR, MLS, XW), pp. 2743–2745.
CIKMCIKM-2012-ChenW #automation #classification #naive bayes
Automated feature weighting in naive bayes for high-dimensional data classification (LC, SW), pp. 1243–1252.
CIKMCIKM-2012-ComarLSNT #detection #kernel #linear
Weighted linear kernel with tree transformed features for malware detection (PMC, LL, SS, AN, PNT), pp. 2287–2290.
CIKMCIKM-2012-HaiCC #mining
One seed to find them all: mining opinion features via association (ZH, KC, GC), pp. 255–264.
CIKMCIKM-2012-MacdonaldSO #learning #on the #query #rank
On the usefulness of query features for learning to rank (CM, RLTS, IO), pp. 2559–2562.
CIKMCIKM-2012-QuanzH #generative #learning #multi #named
CoNet: feature generation for multi-view semi-supervised learning with partially observed views (BQ, JH), pp. 1273–1282.
CIKMCIKM-2012-VouzoukidouAC #query
Processing continuous text queries featuring non-homogeneous scoring functions (NV, BA, VC), pp. 1065–1074.
CIKMCIKM-2012-WangZLL #categorisation #feature model
Feature selection based on term frequency and T-test for text categorization (DW, HZ, RL, WL), pp. 1482–1486.
CIKMCIKM-2012-XiangFWHR #corpus #detection #scalability #topic #twitter
Detecting offensive tweets via topical feature discovery over a large scale twitter corpus (GX, BF, LW, JIH, CPR), pp. 1980–1984.
CIKMCIKM-2012-XuXLW #classification
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-YinPZH #multi #summary
Query-focused multi-document summarization based on query-sensitive feature space (WY, YP, FZ, LH), pp. 1652–1656.
CIKMCIKM-2012-ZhuYCQ #approach #classification #feature model #graph
Graph classification: a diversified discriminative feature selection approach (YZ, JXY, HC, LQ), pp. 205–214.
ICMLICML-2012-DanylukA #feature model #probability
Feature Selection via Probabilistic Outputs (APD, NA), p. 127.
ICMLICML-2012-DuanXT #adaptation #learning
Learning with Augmented Features for Heterogeneous Domain Adaptation (LD, DX, IWT), p. 89.
ICMLICML-2012-FarabetCNL #learning #multi #parsing
Scene parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers (CF, CC, LN, YL), p. 241.
ICMLICML-2012-GoodfellowCB #learning #scalability
Large-Scale Feature Learning With Spike-and-Slab Sparse Coding (IJG, ACC, YB), p. 180.
ICMLICML-2012-JawanpuriaN #learning
A Convex Feature Learning Formulation for Latent Task Structure Discovery (PJ, JSN), p. 199.
ICMLICML-2012-KoepkeB #performance #predict
Fast Prediction of New Feature Utility (HAK, MB), p. 130.
ICMLICML-2012-LeRMDCCDN #learning #scalability #using
Building high-level features using large scale unsupervised learning (QVL, MR, RM, MD, GC, KC, JD, AYN), p. 69.
ICMLICML-2012-Memisevic #learning #multi #on the
On multi-view feature learning (RM), p. 140.
ICMLICML-2012-ZhaiTTO
Discovering Support and Affiliated Features from Very High Dimensions (YZ, MT, IWT, YSO), p. 226.
ICMLICML-2012-Zhu #feature model #modelling #parametricity #predict
Max-Margin Nonparametric Latent Feature Models for Link Prediction (JZ), p. 154.
ICPRICPR-2012-0007B #classification #feature model #image #kernel #multi
Multiple local kernel integrated feature selection for image classification (YS, BB), pp. 2230–2233.
ICPRICPR-2012-AiDHC #analysis #component #feature model #independence #multi
Multiple feature selection and fusion based on generalized N-dimensional independent component analysis (DA, GD, XHH, YWC), pp. 971–974.
ICPRICPR-2012-AtupelageNYAHS #multi
Multifractal feature descriptor for grading Hepatocellular carcinoma (CA, HN, MY, TA, AH, MS), pp. 129–132.
ICPRICPR-2012-AyechZ #clustering #feature model #image #modelling #segmentation #statistics
Terahertz image segmentation based on K-harmonic-means clustering and statistical feature extraction modeling (MWA, DZ), pp. 222–225.
ICPRICPR-2012-BaiZX #detection #linear #multi
Multi scale multi structuring element top-hat transform for linear feature detection (XB, FZ, BX), pp. 1920–1923.
ICPRICPR-2012-BeinruckerDB #feature model
Early stopping for mutual information based feature selection (AB, UD, GB), pp. 975–978.
ICPRICPR-2012-CataldoBFM #classification #image
Applying textural features to the classification of HEp-2 cell patterns in IIF images (SDC, AB, EF, EM), pp. 3349–3352.
ICPRICPR-2012-ChangWCYH #assessment #image #quality
Sparse feature fidelity for image quality assessment (HwC, MhW, SqC, HY, ZjH), pp. 1619–1622.
ICPRICPR-2012-ChengLWTCBWS #detection
Peripapillary atrophy detection by biologically inspired feature (JC, JL, DWKW, NMT, CYlC, MB, TYW, SMS), pp. 53–56.
ICPRICPR-2012-ChenH0N #classification #documentation
Structured document classification by matching local salient features (SC, YH, JS, SN), pp. 653–656.
ICPRICPR-2012-ChumM #estimation
Homography estimation from correspondences of local elliptical features (OC, JM), pp. 3236–3239.
ICPRICPR-2012-CoustatyUO #image
Extraction of light and specific features for historical image indexing and matching (MC, SU, JMO), pp. 1326–1329.
ICPRICPR-2012-DahmBCG #detection #morphism
Topological features and iterative node elimination for speeding up subgraph isomorphism detection (ND, HB, TC, YG), pp. 1164–1167.
ICPRICPR-2012-FernandezT #documentation #segmentation #using
Document segmentation using Relative Location Features (FCF, ORT), pp. 1562–1565.
ICPRICPR-2012-GhoshC #analysis #automation #classification
Feature analysis for automatic classification of HEp-2 florescence patterns : Computer-Aided Diagnosis of Auto-immune diseases (SG, VC), pp. 174–177.
ICPRICPR-2012-GlazerLM #detection
Feature shift detection (AG, ML, SM), pp. 1383–1386.
ICPRICPR-2012-GonfausGGRG #classification #geometry #using
Edge classification using photo-geometric features (JMG, TG, AG, FXR, JG), pp. 1497–1500.
ICPRICPR-2012-GossowWB #invariant
Distinctive texture features from perspective-invariant keypoints (DG, DW, MB), pp. 2764–2767.
ICPRICPR-2012-GutmannH #architecture #feature model #image #learning
Learning a selectivity-invariance-selectivity feature extraction architecture for images (MG, AH), pp. 918–921.
ICPRICPR-2012-HesseGGE #multi #recognition #using
Multi-view facial expression recognition using local appearance features (NH, TG, HG, HKE), pp. 3533–3536.
ICPRICPR-2012-HidoM #feature model #predict
Temporal feature selection for time-series prediction (SH, TM), pp. 3557–3560.
ICPRICPR-2012-HouHZQ #named #paradigm #retrieval
Bag-of-feature-graphs: A new paradigm for non-rigid shape retrieval (TH, XH, MZ, HQ), pp. 1513–1516.
ICPRICPR-2012-HuangLC #clustering #feature model #kernel #multi #self
Cluster-dependent feature selection by multiple kernel self-organizing map (KCH, YYL, JZC), pp. 589–592.
ICPRICPR-2012-HuangLT #invariant #learning #recognition
Learning modality-invariant features for heterogeneous face recognition (LH, JL, YPT), pp. 1683–1686.
ICPRICPR-2012-JensenED #classification #feature model
Classification of kinematic golf putt data with emphasis on feature selection (UJ, BE, FD), pp. 1735–1738.
ICPRICPR-2012-JiangFZT #detection #random
Active Shape Model with random forest for facial features detection (WJ, YF, ZZ, YT), pp. 593–596.
ICPRICPR-2012-JungN #modelling #refinement
Model-based feature refinement by ellipsoidal face tracking (SUJ, MSN), pp. 1209–1212.
ICPRICPR-2012-KannalaR #image #named #statistics
BSIF: Binarized statistical image features (JK, ER), pp. 1363–1366.
ICPRICPR-2012-KawaiMHIY #identification #using
Person re-identification using view-dependent score-level fusion of gait and color features (RK, YM, CH, HI, YY), pp. 2694–2697.
ICPRICPR-2012-KemmlerD
Finding discriminative features for Raman spectroscopy (MK, JD), pp. 1823–1826.
ICPRICPR-2012-KisilevFWTN #image
DFlow and DField: New features for capturing object and image relationships (PK, DF, EW, AT, YN), pp. 3590–3593.
ICPRICPR-2012-KunchevaF #detection #feature model #multi #streaming
PCA feature extraction for change detection in multidimensional unlabelled streaming data (LIK, WJF), pp. 1140–1143.
ICPRICPR-2012-LankinenKK #categorisation #comparison #detection #visual notation
A comparison of local feature detectors and descriptors for visual object categorization by intra-class repeatability and matching (JL, VK, JKK), pp. 780–783.
ICPRICPR-2012-LeiLL #analysis #feature model #linear #performance #recognition
Efficient feature selection for linear discriminant analysis and its application to face recognition (ZL, SL, SZL), pp. 1136–1139.
ICPRICPR-2012-LiangYCJ #evaluation #representation
Evaluation of local feature descriptors and their combination for pedestrian representation (JL, QY, JC, JJ), pp. 2496–2499.
ICPRICPR-2012-LiSY #detection #invariant
A Fully Affine Invariant Feature detector (WL, ZS, JY), pp. 2768–2771.
ICPRICPR-2012-LiuC #3d
3D tracking of deformable surface by propagating feature correspondences (YL, YQC), pp. 2202–2205.
ICPRICPR-2012-LiuKWJ #recognition
Action recognition with discriminative mid-level features (CL, YK, XW, YJ), pp. 3366–3369.
ICPRICPR-2012-LiuSZ #feature model #graph
Sparsity Score: A new filter feature selection method based on graph (ML, DS, DZ), pp. 959–962.
ICPRICPR-2012-LiuW12a #feature model #kernel
Unsupervised discriminative feature selection in a kernel space via L2, 1-norm minimization (YL, YW), pp. 1205–1208.
ICPRICPR-2012-LiuXAR #geometry #recognition #using
Hand posture recognition using finger geometric feature (LL, JX, HA, XR), pp. 565–568.
ICPRICPR-2012-LiVBB #clustering #learning #using
Feature learning using Generalized Extreme Value distribution based K-means clustering (ZL, OV, HB, RB), pp. 1538–1541.
ICPRICPR-2012-LiXLL #independence #recognition
Combination of global and local baseline-independent features for offline Arabic handwriting recognition (NL, XX, WL, KML), pp. 713–716.
ICPRICPR-2012-LiYLKZL #classification #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 #classification
A new feature and associated optimal spatial filter for EEG signal classification: Waveform Length (FL), pp. 1302–1305.
ICPRICPR-2012-MartelliCBTM #detection #paradigm #similarity
Joining feature-based and similarity-based pattern description paradigms for object detection (SM, MC, LB, DT, VM), pp. 2702–2705.
ICPRICPR-2012-MiaoLZ #fault #feature model #predict
Cost-sensitive feature selection with application in software defect prediction (LM, ML, DZ), pp. 967–970.
ICPRICPR-2012-MiksikM #detection #evaluation #performance
Evaluation of local detectors and descriptors for fast feature matching (OM, KM), pp. 2681–2684.
ICPRICPR-2012-MoZW #classification #learning
Enhancing cross-view object classification by feature-based transfer learning (YM, ZZ, YW), pp. 2218–2221.
ICPRICPR-2012-NayefAB #learning
Learning feature weights of symbols, with application to symbol spotting (NN, MZA, TMB), pp. 2371–2374.
ICPRICPR-2012-NguyenFMO #image #performance #retrieval
Mapping high dimensional features onto Hilbert curve: Applying to fast image retrieval (GN, PF, RM, JMO), pp. 425–428.
ICPRICPR-2012-NiigakiSM #detection #using
Circular object detection based on separability and uniformity of feature distributions using Bhattacharyya Coefficient (HN, JS, MM), pp. 2009–2012.
ICPRICPR-2012-PanZXQ #2d #category theory #detection
Improved generic categorical object detection fusing depth cue with 2D appearance and shape features (HP, YZ, SX, KQ), pp. 1467–1470.
ICPRICPR-2012-PinquierKLGMBGD #multi #process #recognition #smarttech
Strategies for multiple feature fusion with Hierarchical HMM: Application to activity recognition from wearable audiovisual sensors (JP, SK, LL, PG, RM, JBP, YG, JFD), pp. 3192–3195.
ICPRICPR-2012-Schmidt-HackenbergYB #detection #image #visual notation
Visual cortex inspired features for object detection in X-ray images (LSH, MRY, TMB), pp. 2573–2576.
ICPRICPR-2012-SlimaneZKAHI #recognition
New features for complex Arabic fonts in cascading recognition system (FS, OZ, SK, AMA, JH, RI), pp. 738–741.
ICPRICPR-2012-TangHW #detection #multi #recognition
Hand-dorsa vein recognition based on multi-level keypoint detection and local feature matching (YT, DH, YW), pp. 2837–2840.
ICPRICPR-2012-TanK #identification #image
Human identification from at-a-distance images by simultaneously exploiting iris and periocular features (CWT, AK), pp. 553–556.
ICPRICPR-2012-TanLZ #dataset
The dataset system of Economic Dispute handwritten (DSEDH) based on stroke shape and structure features (JT, JHL, XXZ), pp. 661–664.
ICPRICPR-2012-VieiraLSC #distance #invariant #matrix
Distance matrices as invariant features for classifying MoCap data (AWV, TL, WRS, MFMC), pp. 2934–2937.
ICPRICPR-2012-WakayamaDDIMT #detection #estimation #performance #visual notation
Estimation of the human performance for pedestrian detectability based on visual search and motion features (MW, DD, KD, II, HM, YT), pp. 1940–1943.
ICPRICPR-2012-WangAG #adaptation #feature model #graph #matrix
Adaptive graph regularized Nonnegative Matrix Factorization via feature selection (JW, IA, XG), pp. 963–966.
ICPRICPR-2012-WangCCP #detection #realtime #using
Real-time smoke detection using texture and color features (YW, TWC, RC, NTP), pp. 1727–1730.
ICPRICPR-2012-WangSCPZ #analysis #component #feature model #named
STPCA: Sparse tensor Principal Component Analysis for feature extraction (SW, MS, YHC, EPP, CZ), pp. 2278–2281.
ICPRICPR-2012-WangSCSW #categorisation #representation
Object categorization via sparse representation of local features (JW, XS, RC, MFS, QW), pp. 3005–3008.
ICPRICPR-2012-WangST #feature model #linear #programming #recognition #robust
Robust regularized feature selection for iris recognition via linear programming (LW, ZS, TT), pp. 3358–3361.
ICPRICPR-2012-WongLTYCCBW #approach #automation #graph #locality
Automatic localization of the macula in a supervised graph-based approach with contextual superpixel features (DWKW, JL, NMT, FY, XC, CMGC, MB, TYW), pp. 2063–2066.
ICPRICPR-2012-WuHWT #classification #encoding #image
Group encoding of local features in image classification (ZW, YH, LW, TT), pp. 1505–1508.
ICPRICPR-2012-XuCYSIL #image
Feature-aligned 4D spatiotemporal image registration (HX, PC, WY, AS, SSI, XL), pp. 2639–2642.
ICPRICPR-2012-YamasakiC #classification #recognition #refinement
Confidence-assisted classification result refinement for object recognition featuring TopN-Exemplar-SVM (TY, TC), pp. 1783–1786.
ICPRICPR-2012-YamashitaTHNH #detection #representation
Sparse representation of audio features for sputum detection from lung sounds (TY, ST, KH, YN, SH), pp. 2005–2008.
ICPRICPR-2012-YangLJ #2d #3d #estimation
Face pose estimation with combined 2D and 3D HOG features (JY, WL, YJ), pp. 2492–2495.
ICPRICPR-2012-YeD #learning #predict
Learning features for predicting OCR accuracy (PY, DSD), pp. 3204–3207.
ICPRICPR-2012-ZhangFD #algorithm #multi #recognition
A hierarchical algorithm with multi-feature fusion for facial expression recognition (ZZ, CF, XD), pp. 2363–2366.
ICPRICPR-2012-ZhangFWZJ #image #scalability #using
Scalable image co-segmentation using color and covariance features (SZ, WF, LW, JZ, JJ), pp. 3708–3711.
ICPRICPR-2012-ZhangH #feature model #recognition #using
Face recognition using semi-supervised spectral feature selection (ZZ, ERH), pp. 1294–1297.
ICPRICPR-2012-ZhangH12a #feature model #recognition
Unsupervised spectral feature selection for face recognition (ZZ, ERH), pp. 1787–1790.
ICPRICPR-2012-ZhangLGZ #classification #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-ZhangWBZCZ #detection #feature model
Object detection via foreground contour feature selection and part-based shape model (HZ, JW, XB, JZ, JC, HZ), pp. 2524–2527.
ICPRICPR-2012-ZhangWN #detection #feature model #student
Bayesian feature selection and model detection for student’s t-mixture distributions (HZ, QMJW, TMN), pp. 1631–1634.
ICPRICPR-2012-ZhaoXY #learning #network #speech
Unsupervised Tibetan speech features Learning based on Dynamic Bayesian Networks (YZ, XX, GY), pp. 2319–2322.
ICPRICPR-2012-ZhouWXZM #learning #recognition
Learning weighted features for human action recognition (WZ, CW, BX, ZZ, LM), pp. 1160–1163.
KDDKDD-2012-ChengZAMZZN #multi #predict
Multimedia features for click prediction of new ads in display advertising (HC, RvZ, JA, EM, RZ, YZ, VN), pp. 777–785.
KDDKDD-2012-GongYZ #learning #multi #robust
Robust multi-task feature learning (PG, JY, CZ), pp. 895–903.
KDDKDD-2012-TangL #feature model #social #social media
Unsupervised feature selection for linked social media data (JT, HL), pp. 904–912.
KDDKDD-2012-WoznicaNK #feature model #mining #robust
Model mining for robust feature selection (AW, PN, AK), pp. 913–921.
KDDKDD-2012-YangYLSWY #graph
Feature grouping and selection over an undirected graph (SY, LY, YCL, XS, PW, JY), pp. 922–930.
KDDKDD-2012-YuDSW #feature model #mining #streaming
Mining emerging patterns by streaming feature selection (KY, WD, DAS, XW), pp. 60–68.
KDIRKDIR-2012-IkebeKT #learning #predict #smarttech #using
Friendship Prediction using Semi-supervised Learning of Latent Features in Smartphone Usage Data (YI, MK, HT), pp. 199–205.
KEODKEOD-2012-MykowieckaM #clustering
Clustering of Medical Terms based on Morpho-syntactic Features (AM, MM), pp. 214–219.
MLDMMLDM-2012-StaroszczykOM #analysis #comparative #feature model #recognition
Comparative Analysis of Feature Selection Methods for Blood Cell Recognition in Leukemia (TS, SO, TM), pp. 467–481.
SEKESEKE-2012-GaoKN #feature model #metric
Stability of Filter-Based Feature Selection Methods for Imbalanced Software Measurement Data (KG, TMK, AN), pp. 74–79.
SEKESEKE-2012-ShenHTGZ #feature model #logic #modelling #verification
Feature modeling and Verification based on Description Logics (GS, ZH, CT, QG, WZ), pp. 422–425.
SIGIRSIGIR-2012-FangHC #graph
Confidence-aware graph regularization with heterogeneous pairwise features (YF, BJPH, KCCC), pp. 951–960.
SIGIRSIGIR-2012-HongLYZZ #automation #novel #what
What reviews are satisfactory: novel features for automatic helpfulness voting (YH, JL, JMY, QZ, GZ), pp. 495–504.
SIGIRSIGIR-2012-LiebermanS #adaptation #streaming
Adaptive context features for toponym resolution in streaming news (MDL, HS), pp. 731–740.
SIGIRSIGIR-2012-TanGS #exclamation #identification
$100, 000 prize jackpot. call now!: identifying the pertinent features of SMS spam (HT, NG, MS), pp. 1175–1176.
ECMFAECMFA-2012-RathHV #emf #query
Derived Features for EMF by Integrating Advanced Model Queries (IR, ÁH, DV), pp. 102–117.
MODELSMoDELS-2012-AranegaEM #feature model #model transformation #using
Using Feature Model to Build Model Transformation Chains (VA, AE, SM), pp. 562–578.
MODELSMoDELS-2012-SchroeterLW #feature model #modelling #multi
Multi-perspectives on Feature Models (JS, ML, TW), pp. 252–268.
MODELSMoDELS-2012-AranegaEM #feature model #model transformation #using
Using Feature Model to Build Model Transformation Chains (VA, AE, SM), pp. 562–578.
MODELSMoDELS-2012-SchroeterLW #feature model #modelling #multi
Multi-perspectives on Feature Models (JS, ML, TW), pp. 252–268.
TOOLSTOOLS-EUROPE-2012-OlszakBJV #detection #quantifier
Detection of Seed Methods for Quantification of Feature Confinement (AO, EB, BNJ, JV), pp. 252–268.
GPCEGPCE-2012-RysselPK #feature model #modelling #reasoning
Reasoning of feature models from derived features (UR, JP, KK), pp. 21–30.
POPLPOPL-2012-Moore #proving #theorem proving
Meta-level features in an industrial-strength theorem prover (JSM), pp. 425–426.
RERE-2012-AroraSR #feature model #interactive #nondeterminism
Resolving uncertainty in automotive feature interactions (SA, PS, SR), pp. 21–30.
RERE-2012-LiZ0 #configuration management #feature model #modelling #named
MbFM: A matrix-based tool for modeling and configuring feature models (LL, HZ, WZ), pp. 325–326.
RERE-2012-ShakerAW #feature model #modelling #requirements
A feature-oriented requirements modelling language (PS, JMA, SW), pp. 151–160.
RERE-2012-Yi0ZJM #constraints #feature model #mining #modelling
Mining binary constraints in the construction of feature models (LY, WZ, HZ, ZJ, HM), pp. 141–150.
RERE-2012-YiZ0J #collaboration #feature model #modelling #named
CoFM: An environment for collaborative feature modeling (LY, HZ, WZ, ZJ), pp. 317–318.
REFSQREFSQ-2012-FrickerS #case study #industrial #release planning
Release Planning with Feature Trees: Industrial Case (SF, SS), pp. 288–305.
SACSAC-2012-AvalhaisSRT #difference #image #retrieval #search-based
Image retrieval employing genetic dissimilarity weighting and feature space transformation functions (LPSA, SFdS, JFRJ, AJMT), pp. 1012–1017.
SACSAC-2012-CunhaSAP #summary #video
Rushes video summarization based on spatio-temporal features (TOC, FGHdS, AdAA, GLP), pp. 45–50.
SACSAC-2012-HuMB12a #clustering #documentation
Enhancing semi-supervised document clustering with feature supervision (YH, EEM, JB), pp. 929–936.
SACSAC-2012-NunesCM #learning #network #similarity #social
Resolving user identities over social networks through supervised learning and rich similarity features (AN, PC, BM), pp. 728–729.
ICSEICSE-2012-NovaisNLCDGM #comprehension #evolution #industrial #interactive #on the #visualisation
On the proactive and interactive visualization for feature evolution comprehension: An industrial investigation (RLN, CN, CANL, EC, FD, AG, MGM), pp. 1044–1053.
ICSEICSE-2012-OuelletMSG #feature model
Locating features in dynamically configured avionics software (MO, EM, NS, MG), pp. 1453–1454.
ICSEICSE-2012-SiegmundKKABRS #automation #detection #performance #predict
Predicting performance via automated feature-interaction detection (NS, SSK, CK, SA, DSB, MR, GS), pp. 167–177.
PLEASEPLEASE-2012-AcherMHCL #feature model #modelling #tool support
Languages and tools for managing feature models (MA, RM, PH, PC, PL), pp. 25–28.
PLEASEPLEASE-2012-QuintonDHMC #feature model #modelling #using
Using feature modelling and automations to select among cloud solutions (CQ, LD, PH, SM, EC), pp. 17–20.
PLEASEPLEASE-2012-ShimbaraWKKO #testing
Feature-analysis-based selection method for system configuration for system testing (DS, HW, SK, MK, HO), pp. 61–64.
SPLCSPLC-2012-AndersenCSW #feature model #modelling #performance #synthesis
Efficient synthesis of feature models (NA, KC, SS, AW), pp. 106–115.
SPLCSPLC-2012-BragaJBL #certification #feature model #modelling #product line
Incorporating certification in feature modelling of an unmanned aerial vehicle product line (RTVB, OTJ, KRLJCB, JL), pp. 249–258.
SPLCSPLC-2012-El-SharkawyDS #analysis #feature model #modelling
From feature models to decision models and back again an analysis based on formal transformations (SES, SD, KS), pp. 126–135.
SPLCSPLC-2012-GillainFHJS #optimisation
Product portfolio scope optimization based on features and goals (JG, SF, PH, IJ, MS), pp. 161–170.
SPLCSPLC-2012-HofmanSPKB #feature model #modelling #product line
Domain specific feature modeling for software product lines (PH, TS, TP, MK, AB), pp. 229–238.
SPLCSPLC-2012-JohansenHF #algorithm #array #feature model #generative #modelling #scalability
An algorithm for generating t-wise covering arrays from large feature models (MFJ, ØH, FF), pp. 46–55.
SPLCSPLC-2012-NunesGLL #evolution #heuristic #product line
History-sensitive heuristics for recovery of features in code of evolving program families (CN, AG, CJPdL, JL), pp. 136–145.
SPLCSPLC-2012-SeidlHA #co-evolution #modelling #product line
Co-evolution of models and feature mapping in software product lines (CS, FH, UA), pp. 76–85.
SPLCSPLC-2012-SoltaniAGHB #automation #feature model #non-functional #requirements
Automated planning for feature model configuration based on functional and non-functional requirements (SS, MA, DG, MH, EB), pp. 56–65.
OSDIOSDI-2012-BelayBMTMK #cpu #named
Dune: Safe User-level Access to Privileged CPU Features (AB, AB, AJM, DT, DM, CK), pp. 335–348.
ICLPICLP-2012-BacciCFV #automation #functional #logic #specification #synthesis
The additional difficulties for the automatic synthesis of specifications posed by logic features in functional-logic languages (GB, MC, MAF, AV), pp. 144–153.
ECSAECSA-2011-AcherCCMDL #architecture #feature model #modelling #reverse engineering
Reverse Engineering Architectural Feature Models (MA, AC, PC, PM, LD, PL), pp. 220–235.
ECSAECSA-2011-GamezFA #architecture #feature model #modelling
Autonomic Computing Driven by Feature Models and Architecture in FamiWare (NG, LF, MAA), pp. 164–179.
WICSAWICSA-2011-Abu-MatarG #architecture #variability
Feature Based Variability for Service Oriented Architectures (MAM, HG), pp. 302–309.
WICSAWICSA-2011-Kamath #architecture
Capabilities and Features: Linking Business and Application Architectures (SK), pp. 12–21.
ASEASE-2011-AcherCLF #feature model #modelling #slicing
Slicing feature models (MA, PC, PL, RBF), pp. 424–427.
ASEASE-2011-AcherCLF11a #feature model #modelling
Decomposing feature models: language, environment, and applications (MA, PC, PL, RBF), pp. 600–603.
ASEASE-2011-ApelSWRB #detection #feature model #interactive #using #verification
Detection of feature interactions using feature-aware verification (SA, HS, PW, AvR, DB), pp. 372–375.
ASEASE-2011-PohlLP #algorithm #analysis #automation #comparison #feature model #modelling #performance
A performance comparison of contemporary algorithmic approaches for automated analysis operations on feature models (RP, KL, KP), pp. 313–322.
ASEASE-2011-RasoolM #design pattern #detection #flexibility
Flexible design pattern detection based on feature types (GR, PM), pp. 243–252.
ASEASE-2011-SoltaniAHGB #automation #feature model
Automated planning for feature model configuration based on stakeholders’ business concerns (SS, MA, MH, DG, EB), pp. 536–539.
CASECASE-2011-BoemPFP #clustering #distance #multi #using
Multi-feature trajectory clustering using Earth Mover’s Distance (FB, FAP, GF, TP), pp. 310–315.
CASECASE-2011-ColP #detection #performance #recursion
Fast and accurate object detection by means of recursive monomial feature elimination and cascade of SVM (LDC, FAP), pp. 304–309.
CASECASE-2011-SenoussiCDZ #detection #fault #feature model #process
Feature selection for fault detection systems: Application to the Tennessee Eastman Process (HS, BCM, MD, NZ), pp. 189–194.
DACDAC-2011-ClemonsJPSA #embedded #feature model #named
EFFEX: an embedded processor for computer vision based feature extraction (JC, AJ, RP, SS, TMA), pp. 1020–1025.
DACDAC-2011-KadryMGAK #approach #challenge #design #effectiveness #verification
Facing the challenge of new design features: an effective verification approach (WK, RM, AG, EA, CAK), pp. 842–847.
DATEDATE-2011-ChenO #analysis #fault #image #statistics
Diagnosing scan chain timing faults through statistical feature analysis of scan images (MC, AO), pp. 185–190.
DATEDATE-2011-FerentD #automation #design #similarity
A symbolic technique for automated characterization of the uniqueness and similarity of analog circuit design features (CF, AD), pp. 1212–1217.
DRRDRR-2011-BockholtCM #documentation #image #retrieval #segmentation
Document image retrieval with morphology-based segmentation and features combination (TCB, GDCC, CABM), pp. 1–10.
DRRDRR-2011-FanSNMH #feature model #recognition
Natural scene logo recognition by joint boosting feature selection in salient regions (WF, JS, SN, AM, YH), pp. 1–10.
DRRDRR-2011-LiuZ #image #mobile #using
Segmenting texts from outdoor images taken by mobile phones using color features (ZL, HZ), pp. 1–10.
DRRDRR-2011-SiddiqiKV #analysis #identification
Feature relevance analysis for writer identification (IS, KK, NV), pp. 1–10.
HTHT-2011-WoenselCT #approach #on the fly
A generic approach for on-the-fly adding of context-aware features to existing websites (WVW, SC, ODT), pp. 143–152.
ICDARICDAR-2011-AbediF #analysis #documentation #image #locality #string #using
Localization of Digit Strings in Farsi/Arabic Document Images Using Structural Features and Syntactical Analysis (AA, KF), pp. 728–733.
ICDARICDAR-2011-AlmazanFV #feature model #recognition
A Non-rigid Feature Extraction Method for Shape Recognition (JA, AF, EV), pp. 987–991.
ICDARICDAR-2011-AtanasiuLV #novel #retrieval #using
Writer Retrieval — Exploration of a Novel Biometric Scenario Using Perceptual Features Derived from Script Orientation (VA, LLS, NV), pp. 628–632.
ICDARICDAR-2011-ChaabouniBKAA11a #feature model #identification #online
Combining of Off-line and On-line Feature Extraction Approaches for Writer Identification (AC, HB, MK, AMA, HEA), pp. 1299–1303.
ICDARICDAR-2011-ChoSLK #multi
Scene Text Extraction by Superpixel CRFs Combining Multiple Character Features (MSC, JHS, SL, JHK), pp. 1034–1038.
ICDARICDAR-2011-CoatesCCSSWWN #detection #image #learning #recognition
Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning (AC, BC, CC, SS, BS, TW, DJW, AYN), pp. 440–445.
ICDARICDAR-2011-GaoWJ #2d #optimisation #recognition
A New Feature Optimization Method Based on Two-Directional 2DLDA for Handwritten Chinese Character Recognition (XG, WW, LJ), pp. 232–236.
ICDARICDAR-2011-GarzSD #analysis #layout #using
Layout Analysis for Historical Manuscripts Using Sift Features (AG, RS, MD), pp. 508–512.
ICDARICDAR-2011-GatosKP #adaptation #recognition #word
Adaptive Zoning Features for Character and Word Recognition (BG, ALK, AP), pp. 1160–1164.
ICDARICDAR-2011-HebertPN #multi
Continuous CRF with Multi-scale Quantization Feature Functions Application to Structure Extraction in Old Newspaper (DH, TP, SN), pp. 493–497.
ICDARICDAR-2011-HuZ #online #recognition #using
HMM-Based Recognition of Online Handwritten Mathematical Symbols Using Segmental K-Means Initialization and a Modified Pen-Up/Down Feature (LH, RZ), pp. 457–462.
ICDARICDAR-2011-IwamuraKK #image #multi #recognition #using
Recognition of Multiple Characters in a Scene Image Using Arrangement of Local Features (MI, TK, KK), pp. 1409–1413.
ICDARICDAR-2011-JamilSAR #image #locality #video
Edge-Based Features for Localization of Artificial Urdu Text in Video Images (AJ, IS, FA, AR), pp. 1120–1124.
ICDARICDAR-2011-LouradourK #categorisation #documentation #feature model #image #performance
Sample-Dependent Feature Selection for Faster Document Image Categorization (JL, CK), pp. 309–313.
ICDARICDAR-2011-LuangvilayZN #online
An On-line Handwritten Text Search Method Based on Directional Feature Matching (PL, BZ, MN), pp. 683–686.
ICDARICDAR-2011-NatarajanBPKSN #recognition
Baseline Dependent Percentile Features for Offline Arabic Handwriting Recognition (PN, DB, RP, MK, KS, PN), pp. 329–333.
ICDARICDAR-2011-NguyenB #2d #feature model #verification
An Application of the 2D Gaussian Filter for Enhancing Feature Extraction in Off-line Signature Verification (VN, MB), pp. 339–343.
ICDARICDAR-2011-ParodiGB #approach #feature model #invariant #verification
A Circular Grid-Based Rotation Invariant Feature Extraction Approach for Off-line Signature Verification (MP, JCG, AB), pp. 1289–1293.
ICDARICDAR-2011-Saund #approach #graph #image #maintenance
A Graph Lattice Approach to Maintaining Dense Collections of Subgraphs as Image Features (ES), pp. 1069–1074.
ICDARICDAR-2011-SimistiraPSK #segmentation #word
Enhancing Handwritten Word Segmentation by Employing Local Spatial Features (FS, VP, TS, VK), pp. 1314–1318.
ICDARICDAR-2011-UchidaSF #generative
A Generative Model for Handwritings Based on Enhanced Feature Desynchronization (SU, TS, YF), pp. 589–593.
ICDARICDAR-2011-VinelDA #feature model #linear #optimisation #random
Joint Optimization of Hidden Conditional Random Fields and Non Linear Feature Extraction (AV, TMTD, TA), pp. 513–517.
ICDARICDAR-2011-XuDPL #grid #independence #recognition
An Improved Method Based on Weighted Grid Micro-structure Feature for Text-Independent Writer Recognition (LX, XD, LP, XL), pp. 638–642.
CSMRCSMR-2011-AndradeRGSRB #flexibility #implementation
Assessing Idioms for Implementing Features with Flexible Binding Times (RA, MR, VG, LS, HR, PB), pp. 231–240.
ICPCICPC-2011-DitGPA #feature model #identifier #question
Can Better Identifier Splitting Techniques Help Feature Location? (BD, LG, DP, GA), pp. 11–20.
ICPCICPC-2011-JurgensFHDVP #evolution #feature model #profiling
Feature Profiling for Evolving Systems (EJ, MF, MH, FD, RV, KHP), pp. 171–180.
ICSMEICSM-2011-WangPXZ #case study #feature model #process
An exploratory study of feature location process: Distinct phases, recurring patterns, and elementary actions (JW, XP, ZX, WZ), pp. 213–222.
ICSMEICSM-2011-YousefiS #distributed #identification #mining
Identifying distributed features in SOA by mining dynamic call trees (AY, KS), pp. 73–82.
MSRMSR-2011-CallauRTR #developer #how #programming language #smalltalk
How developers use the dynamic features of programming languages: the case of smalltalk (OC, RR, ÉT, DR), pp. 23–32.
MSRMSR-2011-ParninBM #how #java
Java generics adoption: how new features are introduced, championed, or ignored (CP, CB, ERMH), pp. 3–12.
WCREWCRE-2011-HaslingerLE #feature model #modelling #reverse engineering #set #source code
Reverse Engineering Feature Models from Programs’ Feature Sets (ENH, RELH, AE), pp. 308–312.
WCREWCRE-2011-OlszakJ #comprehension #legacy
Understanding Legacy Features with Featureous (AO, BNJ), pp. 435–436.
WCREWCRE-2011-OlszakRJ #java #runtime
Meta-Level Runtime Feature Awareness for Java (AO, MR, BNJ), pp. 271–274.
WCREWCRE-2011-PosnettHD #fault #question
Got Issues? Do New Features and Code Improvements Affect Defects? (DP, AH, PTD), pp. 211–215.
SEFMSEFM-2011-MuscheviciPC #composition #modelling #product line
Modular Modelling of Software Product Lines with Feature Nets (RM, JP, DC), pp. 318–333.
AGTIVEAGTIVE-2011-RungeET #algebra #graph transformation #specification
AGG 2.0 — New Features for Specifying and Analyzing Algebraic Graph Transformations (OR, CE, GT), pp. 81–88.
HCIDHM-2011-RupprechtHB #automation
Automatic Face Feature Points Extraction (DR, SH, RB), pp. 186–194.
HCIDUXU-v2-2011-WatanabeYHA #user interface #web
Study of User Interface for Browsing Web Contents That Considers the Cognitive Features of Older Users (MW, SY, RH, YA), pp. 60–67.
HCIHCD-2011-NazemiBK #graph #taxonomy #visual notation #visualisation
User-Oriented Graph Visualization Taxonomy: A Data-Oriented Examination of Visual Features (KN, MB, AK), pp. 576–585.
HCIHIMI-v1-2011-MurakamiK #music #parametricity #process
Auditory Feature Parameters for Music Based on Human Auditory Processes (MM, TK), pp. 612–617.
HCIIDGD-2011-ChenCC11b #identification #user interface
Identifying the Features of Friendly User Interfaces from Emotional Perspectives (LCC, PYC, YMC), pp. 293–301.
HCIIDGD-2011-YehL #design
Applying Local Culture Features into Creative Craft Products Design (MLY, PHL), pp. 114–122.
HCIOCSC-2011-RahimifarS #chat #persistent
Features to Support Persistent Chat Conversation (MR, SSS), pp. 261–266.
HCIOCSC-2011-TanT #design #perspective
Impact of Blog Design Features on Blogging Satisfaction: An Impression Management Perspective (WKT, HHT), pp. 130–139.
ICEISICEIS-v1-2011-MasadaSO #clustering #documentation #feature model #string
Documents as a Bag of Maximal Substrings — An Unsupervised Feature Extraction for Document Clustering (TM, YS, KO), pp. 5–13.
ICEISICEIS-v1-2011-SantosP #data mining #mining #preprocessor #ubiquitous
Enabling Ubiquitous Data Mining in Intensive Care — Features Selection and Data Pre-processing (MS, FP), pp. 261–266.
ICEISICEIS-v3-2011-XiongNF #component #composition #feature model #research
Research on Component Composition based on Feature Model (LRX, ZN, JF), pp. 214–222.
ICEISICEIS-v4-2011-DavisC11a #data transformation #logic #metadata #modelling
Variant Logic Meta-data Management for Model Driven Applications — Allows Unlimited End User Configuration and Customisation of All Meta-data EIS Application Features (JD, EC), pp. 395–400.
CIKMCIKM-2011-Ando #encoding #relational #using
Latent feature encoding using dyadic and relational data (SA), pp. 2201–2204.
CIKMCIKM-2011-BanerjeeC #distributed #feature model #privacy #using
Privacy preserving feature selection for distributed data using virtual dimension (MB, SC), pp. 2281–2284.
CIKMCIKM-2011-ChengKGSH #automation #generative
Automated feature generation from structured knowledge (WC, GK, TG, DHS, RH), pp. 1395–1404.
CIKMCIKM-2011-GuH #feature model #network #towards
Towards feature selection in network (QG, JH), pp. 1175–1184.
CIKMCIKM-2011-GuLH #correlation #feature model #multi
Correlated multi-label feature selection (QG, ZL, JH), pp. 1087–1096.
CIKMCIKM-2011-IslamABR #experience #visual notation #web
Tightly coupling visual and linguistic features for enriching audio-based web browsing experience (MAI, FA, YB, IVR), pp. 2085–2088.
CIKMCIKM-2011-LeeLSY #difference #robust #symmetry #video
Robust video fingerprinting based on hierarchical symmetric difference feature (JL, SL, YS, WY), pp. 2089–2092.
CIKMCIKM-2011-LiuCZH #learning #random
Learning conditional random fields with latent sparse features for acronym expansion finding (JL, JC, YZ, YH), pp. 867–872.
CIKMCIKM-2011-LiuWZ #clustering #feature model #using
Feature selection using hierarchical feature clustering (HL, XW, SZ), pp. 979–984.
CIKMCIKM-2011-TariqK #feature model #performance
Fast supervised feature extraction by term discrimination information pooling (AT, AK), pp. 2233–2236.
CIKMCIKM-2011-WangHJT #categorisation #image #learning #metric #multi #performance
Efficient lp-norm multiple feature metric learning for image categorization (SW, QH, SJ, QT), pp. 2077–2080.
CIKMCIKM-2011-XuSPZ #kernel #named #performance
TAKES: a fast method to select features in the kernel space (YX, FS, WP, JZ), pp. 683–692.
ECIRECIR-2011-Carrillo-de-AlbornozPGD #analysis #bibliography #mining #rating #sentiment
A Joint Model of Feature Mining and Sentiment Analysis for Product Review Rating (JCdA, LP, PG, AD), pp. 55–66.
ECIRECIR-2011-GeraniKCC #retrieval #using
Personal Blog Retrieval Using Opinion Features (SG, MK, MJC, FC), pp. 747–750.
ECIRECIR-2011-JagarlamudiB #feature model #similarity
Fractional Similarity: Cross-Lingual Feature Selection for Search (JJ, PNB), pp. 226–237.
ECIRECIR-2011-KadarI #adaptation #categorisation
Domain Adaptation for Text Categorization by Feature Labeling (CK, JI), pp. 424–435.
ECIRECIR-2011-MoshfeghiJ #collaboration #recommendation
Role of Emotional Features in Collaborative Recommendation (YM, JMJ), pp. 738–742.
ECIRECIR-2011-NeumayerMN #categorisation #feature model
Combination of Feature Selection Methods for Text Categorisation (RN, RM, KN), pp. 763–766.
ICMLICML-2011-ChenWC #automation #composition
Automatic Feature Decomposition for Single View Co-training (MC, KQW, YC), pp. 953–960.
ICMLICML-2011-GeramifardDRRH #dependence #online
Online Discovery of Feature Dependencies (AG, FD, JR, NR, JPH), pp. 881–888.
ICMLICML-2011-GuanDJ #feature model #probability
A Unified Probabilistic Model for Global and Local Unsupervised Feature Selection (YG, JGD, MIJ), pp. 1073–1080.
ICMLICML-2011-JiangR #feature model
Eigenvalue Sensitive Feature Selection (YJ, JR), pp. 89–96.
ICMLICML-2011-KangGS #learning #multi
Learning with Whom to Share in Multi-task Feature Learning (ZK, KG, FS), pp. 521–528.
ICMLICML-2011-Reyzin #predict
Boosting on a Budget: Sampling for Feature-Efficient Prediction (LR), pp. 529–536.
ICMLICML-2011-RifaiVMGB #feature model
Contractive Auto-Encoders: Explicit Invariance During Feature Extraction (SR, PV, XM, XG, YB), pp. 833–840.
ICMLICML-2011-SaxeKCBSN #learning #on the #random
On Random Weights and Unsupervised Feature Learning (AMS, PWK, ZC, MB, BS, AYN), pp. 1089–1096.
ICMLICML-2011-SmallWBT #learning
The Constrained Weight Space SVM: Learning with Ranked Features (KS, BCW, CEB, TAT), pp. 865–872.
ICMLICML-2011-ZhongK #automation #modelling #performance
Efficient Sparse Modeling with Automatic Feature Grouping (WZ, JTK), pp. 9–16.
KDDKDD-2011-ChenRT #adaptation #detection #incremental #learning
Detecting bots via incremental LS-SVM learning with dynamic feature adaptation (FC, SR, PNT), pp. 386–394.
KDDKDD-2011-HendersonGLAETF #graph #mining #recursion #using
It’s who you know: graph mining using recursive structural features (KH, BG, LL, LA, TER, HT, CF), pp. 663–671.
KDDKDD-2011-KongFY #classification #graph
Dual active feature and sample selection for graph classification (XK, WF, PSY), pp. 654–662.
KDDKDD-2011-PereiraB #classification #functional #using
Classification of functional magnetic resonance imaging data using informative pattern features (FP, MB), pp. 940–946.
KDDKDD-2011-ScellatoNM #network #predict #social
Exploiting place features in link prediction on location-based social networks (SS, AN, CM), pp. 1046–1054.
KDDKDD-2011-ZhuLCX #performance #topic
Conditional topical coding: an efficient topic model conditioned on rich features (JZ, NL, NC, EPX), pp. 475–483.
KDIRKDIR-2011-AliDKB #classification #image
Bio-inspired Bags-of-features for Image Classification (WBHA, ED, PK, MB), pp. 277–281.
KDIRKDIR-2011-AlvarezCLP #web
The Spanish Web in Numbers — Main Features of the Spanish Hidden Web (, FC, RLG, VMP), pp. 371–374.
KDIRKDIR-2011-BorcheninovO #embedded #programming #search-based #symbolic computation
Genetic Programming with Embedded Features of Symbolic Computations (YVB, YSO), pp. 476–479.
KDIRKDIR-2011-DoquireV #approach #category theory #feature model #hybrid
An Hybrid Approach to Feature Selection for Mixed Categorical and Continuous Data (GD, MV), pp. 394–401.
KDIRKDIR-2011-FerreiraF #array
Feature Discretization and Selection in Microarray Data (AJF, MATF), pp. 465–469.
KDIRKDIR-2011-GilliesSPW #feature model #ontology #simulation
Gene Ontology based Simulation for Feature Selection (CEG, MRS, NVP, GDW), pp. 294–302.
KDIRKDIR-2011-HagenauLN #feature model #predict
Impact of Feature Selection and Feature Types on Financial Stock Price Prediction (MH, ML, DN), pp. 303–308.
KDIRKDIR-2011-PaliwalP #clustering #documentation #proximity
Utilizing Term Proximity based Features to Improve Text Document Clustering (SP, VP), pp. 537–544.
KEODKEOD-2011-Kral #recognition
Features for Named Entity Recognition in Czech Language (PK), pp. 437–441.
KMISKMIS-2011-SchauerZM #analysis #collaboration #enterprise #open source #tool support
A Feature-based Analysis of Open Source Tools for Enterprise 2.0 — Open Source Tools for Team Collaboration in SMEs (BS, MZ, RM), pp. 57–66.
RecSysRecSys-2011-SekoYMM #behaviour #recommendation #representation #using
Group recommendation using feature space representing behavioral tendency and power balance among members (SS, TY, MM, SyM), pp. 101–108.
SEKESEKE-2011-KimLZKLS #approach #configuration management #modelling #privacy
A Feature-Based Modeling Approach to Configuring Privacy and Temporality in RBAC (SK, YTL, YZ, DKK, LL, VS), pp. 666–671.
SEKESEKE-2011-PossompesDHT #design #diagrams #feature model #implementation #uml
Design of a UML profile for feature diagrams and its tooling implementation (TP, CD, MH, CT), pp. 693–698.
SEKESEKE-2011-ReformatP #approach #evaluation #feature model
Criteria of Human Software Evaluation: Feature Selection Approach (MR, SP), pp. 71–76.
SEKESEKE-2011-ZaatarHH #approach #identification #implementation #product line
An Approach for Identifying and Implementing Aspectual Features inSoftware Product Lines (MAZ, HSH, AEFH), pp. 722–728.
SIGIRSIGIR-2011-BelemMPAG #multi #recommendation
Associative tag recommendation exploiting multiple textual features (FB, EFM, TP, JMA, MAG), pp. 1033–1042.
SIGIRSIGIR-2011-GaoZLLW #feedback #learning
Learning features through feedback for blog distillation (DG, RZ, WL, RYKL, KFW), pp. 1085–1086.
SIGIRSIGIR-2011-GengLWWS #assessment #feature model #quality #statistics #web
Statistical feature extraction for cross-language web content quality assessment (GG, XL, LMW, WW, SS), pp. 1129–1130.
SIGIRSIGIR-2011-JinY #classification #feature model #image #multi
Integrating hierarchical feature selection and classifier training for multi-label image annotation (CJ, CY), pp. 515–524.
SIGIRSIGIR-2011-MoshfeghiPJ #collaboration #semantics #using
Handling data sparsity in collaborative filtering using emotion and semantic based features (YM, BP, JMJ), pp. 625–634.
SIGIRSIGIR-2011-OchiOO #predict #rating #using #word
Rating prediction using feature words extracted from customer reviews (MO, MO, RO), pp. 1205–1206.
MODELSMoDELS-2011-JohansenHF #combinator #feature model #modelling #product line #testing
Properties of Realistic Feature Models Make Combinatorial Testing of Product Lines Feasible (MFJ, ØH, FF), pp. 638–652.
MODELSMoDELS-2011-JohansenHF #combinator #feature model #modelling #product line #testing
Properties of Realistic Feature Models Make Combinatorial Testing of Product Lines Feasible (MFJ, ØH, FF), pp. 638–652.
PLATEAUPLATEAU-2011-SadowskiK #case study #evaluation #heuristic #parallel #programming language
Heuristic evaluation of programming language features: two parallel programming case studies (CS, SK), pp. 9–14.
GPCEGPCE-2011-BatoryHK #composition #feature model #interactive
Feature interactions, products, and composition (DSB, PH, JK), pp. 13–22.
GPCEGPCE-2011-RibeiroQBTBS #dependence #maintenance #on the #product line
On the impact of feature dependencies when maintaining preprocessor-based software product lines (MR, FQ, PB, TT, CB, SS), pp. 23–32.
RERE-2011-BoutkovaH #automation #identification #specification
Semi-automatic identification of features in requirement specifications (EB, FH), pp. 313–318.
RERE-2011-FitzgeraldLF #feature model #predict
Early failure prediction in feature request management systems (CF, EL, AF), pp. 229–238.
RERE-2011-Regnell #evolution #mobile #problem #scalability
Large-scale feature evolution: Problems and solutions from the mobile domain (BR), p. 323.
SACSAC-2011-AcherCLF #domain-specific language #feature model #modelling
A domain-specific language for managing feature models (MA, PC, PL, RBF), pp. 1333–1340.
SACSAC-2011-EbraertSJ #design #diagrams #feature model #implementation
Change-based FODA diagrams: bridging the gap between feature-oriented design and implementation (PE, QDS, DJ), pp. 1345–1352.
SACSAC-2011-HeinenE #incremental #modelling #using
Incremental feature-based mapping from sonar data using Gaussian mixture models (MRH, PME), pp. 1370–1375.
SACSAC-2011-HuMB #clustering #documentation #feature model #interactive
Interactive feature selection for document clustering (YH, EEM, JB), pp. 1143–1150.
SACSAC-2011-KusamaI #music #named #user interface
MusCat: a music browser featuring abstract pictures and zooming user interface (KK, TI), pp. 1222–1228.
SACSAC-2011-LargeronMG #categorisation #feature model
Entropy based feature selection for text categorization (CL, CM, MG), pp. 924–928.
ESEC-FSEESEC-FSE-2011-CostacheKK #design #implementation #process #validation
Design and validation of feature-based process model tailoring: a sample implementation of PDE (DC, GK, MK), pp. 464–467.
GTTSEGTTSE-2011-KastnerA #development #feature model
Feature-Oriented Software Development (CK, SA), pp. 346–382.
ICSEICSE-2011-ApelB #case study #product line
Feature cohesion in software product lines: an exploratory study (SA, DB), pp. 421–430.
ICSEICSE-2011-CataldoH #analysis #development #empirical #feature model #integration
Factors leading to integration failures in global feature-oriented development: an empirical analysis (MC, JDH), pp. 161–170.
ICSEICSE-2011-DumitruGHCMCM #mining #on-demand #recommendation
On-demand feature recommendations derived from mining public product descriptions (HD, MG, NH, JCH, BM, CCH, MM), pp. 181–190.
ICSEICSE-2011-OlivetoGBPL #identification #smell
Identifying method friendships to remove the feature envy bad smell (RO, MG, GB, DP, ADL), pp. 820–823.
ICSEICSE-2011-PengXTYZ #feature model
Iterative context-aware feature location (XP, ZX, XT, YY, WZ), pp. 900–903.
ICSEICSE-2011-SheLBWC #feature model #modelling #reverse engineering
Reverse engineering feature models (SS, RL, TB, AW, KC), pp. 461–470.
ICSEICSE-2011-StengelFAFKD #development #feature model #infinity #interface
View infinity: a zoomable interface for feature-oriented software development (MS, MF, SA, JF, CK, RD), pp. 1031–1033.
SLESLE-2011-KaminskiW #attribute grammar #functional #programming language
Integrating Attribute Grammar and Functional Programming Language Features (TK, EVW), pp. 263–282.
PLEASEPLEASE-2011-SunCGW #approach #feature model #using
Supporting feature model configuration using a demonstration-based approach (YS, HC, JGG, JW), pp. 55–59.
SPLCSPLC-2011-AbbasiHH11a #tool support #workflow
A Toolset for Feature-Based Configuration Workflows (EKA, AH, PH), pp. 65–69.
SPLCSPLC-2011-KatoY #cumulative #feature model #interactive #product line
Variation Management for Software Product Lines with Cumulative Coverage of Feature Interactions (SK, NY), pp. 140–149.
SPLCSPLC-2011-Lopez-HerrejonME #case study #feature model #refactoring #requirements
From Requirements to Features: An Exploratory Study of Feature-Oriented Refactoring (RELH, LMM, AE), pp. 181–190.
SPLCSPLC-2011-ThumKES #feature model #modelling
Abstract Features in Feature Modeling (TT, CK, SE, NS), pp. 191–200.
SPLCSPLC-2011-ThurimellaJ #feature model #plugin
Metadoc Feature Modeler: A Plug-in for IBM Rational DOORS (AKT, DJ), pp. 313–322.
SPLCSPLC-2011-WendeAZK #development #modelling
Feature-Based Customisation of Tool Environments for Model-Driven Software Development (CW, UA, SZ, HK), pp. 45–54.
CBSECBSE-2010-EichbergKMM #component #composition #feature model #modelling #using
Component Composition Using Feature Models (ME, KK, RM, MM), pp. 200–215.
ECSAECSA-2010-ParraCBD #architecture #composition
Feature-Based Composition of Software Architectures (CAP, AC, XB, LD), pp. 230–245.
ASEASE-2010-RatanotayanonCS #feature model #transitive #using
Using transitive changesets to support feature location (SR, HJC, SES), pp. 341–344.
DATEDATE-2010-RathiDGCV #distance #feature model #gpu #implementation
A GPU based implementation of Center-Surround Distribution Distance for feature extraction and matching (AR, MD, WG, RTC, NV), pp. 172–177.
DocEngDocEng-2010-KarolHHA #documentation #feature model #modelling #product line #using
Using feature models for creating families of documents (SK, MH, FH, UA), pp. 259–262.
DocEngDocEng-2010-NamaneSM #feature model #matrix #recognition #using
Degraded dot matrix character recognition using CSM-based feature extraction (AN, EHS, PM), pp. 207–210.
DRRDRR-2010-KnoblockCCGMS #approach
A general approach to discovering, registering, and extracting features from raster maps (CAK, CCC, YYC, AG, MM, CS), pp. 1–10.
DRRDRR-2010-Obafemi-AjayiAF #documentation #learning
Learning shape features for document enhancement (TOA, GA, OF), pp. 1–10.
DRRDRR-2010-OhL #evaluation #feature model #optimisation #recognition
Ant colony optimization with selective evaluation for feature selection in character recognition (ISO, JSL), pp. 1–10.
DRRDRR-2010-YouADRGT #image #multimodal #retrieval #using
Biomedical article retrieval using multimodal features and image annotations in region-based CBIR (DY, SA, DDF, MMR, VG, GRT), pp. 1–10.
SIGMODSIGMOD-2010-CuiTZZ #multi #social #social media
Multiple feature fusion for social media applications (BC, AKHT, CZ, ZZ), pp. 435–446.
ICPCICPC-2010-ChenR #case study #dependence #feature model #graph #using
Case Study of Feature Location Using Dependence Graph, after 10 Years (KC, VR), pp. 1–3.
ICPCICPC-2010-OlszakJ #analysis #java #named
Featureous: A Tool for Feature-Centric Analysis of Java Software (AO, BNJ), pp. 44–45.
ICPCICPC-2010-RatanotayanonCS #data flow #empirical #repository
My Repository Runneth Over: An Empirical Study on Diversifying Data Sources to Improve Feature Search (SR, HJC, SES), pp. 206–215.
ICPCICPC-2010-RevelleDP #data fusion #feature model #mining #using #web
Using Data Fusion and Web Mining to Support Feature Location in Software (MR, BD, DP), pp. 14–23.
ICSMEICSM-2010-BhattacharyaN #debugging #fine-grained #graph #incremental #learning #multi
Fine-grained incremental learning and multi-feature tossing graphs to improve bug triaging (PB, IN), pp. 1–10.
ICSMEICSM-2010-HayashiSS #comprehension #implementation #interactive #named
iFL: An interactive environment for understanding feature implementations (SH, KS, MS), pp. 1–5.
ICSMEICSM-2010-NunesGL #product line
History-sensitive recovery of product line features (CN, AG, CJPdL), pp. 1–2.
WCREWCRE-2010-XueXJ #comprehension #evolution #product line
Understanding Feature Evolution in a Family of Product Variants (YX, ZX, SJ), pp. 109–118.
CAiSECAiSE-2010-StoermerRV #evaluation #implementation
Feature-Based Entity Matching: The FBEM Model, Implementation, Evaluation (HS, NR, NV), pp. 180–193.
CIKMCIKM-2010-BatalH #classification #predict #using
Constructing classification features using minimal predictive patterns (IB, MH), pp. 869–878.
CIKMCIKM-2010-ChatterjeeBR #clustering
Feature subspace transformations for enhancing k-means clustering (AC, SB, PR), pp. 1801–1804.
CIKMCIKM-2010-DingSBVWLC #automation #detection #embedded #feature model #framework #image #using
Automatic detection of craters in planetary images: an embedded framework using feature selection and boosting (WD, TFS, LPCB, RV, YW, ZL, TC), pp. 749–758.
CIKMCIKM-2010-FeiQH #feature model
Regularization and feature selection for networked features (HF, BQ, JH), pp. 1893–1896.
CIKMCIKM-2010-He #classification #learning #sentiment
Learning sentiment classification model from labeled features (YH), pp. 1685–1688.
CIKMCIKM-2010-KaliciakSWP #hybrid #image #novel #retrieval
Novel local features with hybrid sampling technique for image retrieval (LK, DS, NW, JP), pp. 1557–1560.
CIKMCIKM-2010-KatoOOT
Search as if you were in your home town: geographic search by regional context and dynamic feature-space selection (MPK, HO, SO, KT), pp. 1541–1544.
CIKMCIKM-2010-KobdaniSBKH #natural language #re-engineering #relational
Relational feature engineering of natural language processing (HK, HS, AB, WK, GH), pp. 1705–1708.
CIKMCIKM-2010-LiuXCY #classification #feature model #multi
Orientation distance-based discriminative feature extraction for multi-class classification (BL, YX, LC, PSY), pp. 909–918.
CIKMCIKM-2010-NguyenKPT #image #topic
A feature-word-topic model for image annotation (CTN, NK, XHP, TT), pp. 1481–1484.
CIKMCIKM-2010-YangKL #feature model #learning #multi #online
Online learning for multi-task feature selection (HY, IK, MRL), pp. 1693–1696.
CIKMCIKM-2010-ZhaoJHSYL #modelling #ranking
Context modeling for ranking and tagging bursty features in text streams (WXZ, JJ, JH, DS, HY, XL), pp. 1769–1772.
ICMLICML-2010-BoureauPL #analysis #recognition #visual notation
A Theoretical Analysis of Feature Pooling in Visual Recognition (YLB, JP, YL), pp. 111–118.
ICMLICML-2010-GaudelS #feature model #game studies
Feature Selection as a One-Player Game (RG, MS), pp. 359–366.
ICMLICML-2010-MasaeliFD #feature model #reduction
From Transformation-Based Dimensionality Reduction to Feature Selection (MM, GF, JGD), pp. 751–758.
ICMLICML-2010-PetrikTPZ #approximate #feature model #linear #markov #process #source code #using
Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes (MP, GT, RP, SZ), pp. 871–878.
ICMLICML-2010-TanWT #dataset #feature model #learning
Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets (MT, LW, IWT), pp. 1047–1054.
ICMLICML-2010-WuYWD #feature model #online #streaming
Online Streaming Feature Selection (XW, KY, HW, WD), pp. 1159–1166.
ICPRICPR-2010-AbergW #3d #algorithm #clustering
A Memetic Algorithm for Selection of 3D Clustered Features with Applications in Neuroscience (MBÅ, JW), pp. 1076–1079.
ICPRICPR-2010-AdamsWDMBG #feature model #less is more #recognition
Genetic-Based Type II Feature Extraction for Periocular Biometric Recognition: Less is More (JA, DLW, GVD, PEM, KSB, GG), pp. 205–208.
ICPRICPR-2010-AlySTT #multi #recognition #robust #self #similarity #using
Robust Face Recognition Using Multiple Self-Organized Gabor Features and Local Similarity Matching (SKHA, AS, NT, RiT), pp. 2909–2912.
ICPRICPR-2010-ArslanSATY #comparison #data access #image #multi #retrieval
Comparison of Multidimensional Data Access Methods for Feature-Based Image Retrieval (SA, AS, EA, IHT, AY), pp. 3260–3263.
ICPRICPR-2010-AwaisM #recognition
Feature Pairs Connected by Lines for Object Recognition (MA, KM), pp. 3093–3096.
ICPRICPR-2010-BayramogluA #image #recognition #using
Shape Index SIFT: Range Image Recognition Using Local Features (NB, AAA), pp. 352–355.
ICPRICPR-2010-BerrettiBPAD #3d #recognition #set
A Set of Selected SIFT Features for 3D Facial Expression Recognition (SB, ADB, PP, BBA, MD), pp. 4125–4128.
ICPRICPR-2010-BonevEGB #feature model #graph
Information-theoretic Feature Selection from Unattributed Graphs (BB, FE, DG, SB), pp. 930–933.
ICPRICPR-2010-BouchrikaCNMT #detection #people #using
Using Gait Features for Improving Walking People Detection (IB, JNC, MSN, RM, GT), pp. 3097–3100.
ICPRICPR-2010-BuyssensR #learning #verification
Learning Sparse Face Features: Application to Face Verification (PB, MR), pp. 670–673.
ICPRICPR-2010-CakirC #2d #feature model #image #using
Image Feature Extraction Using 2D Mel-Cepstrum (, AEÇ), pp. 674–677.
ICPRICPR-2010-CansizogluB #approach #multi
An Information Fusion Approach for Multiview Feature Tracking (EAC, MB), pp. 1706–1709.
ICPRICPR-2010-CaoZGXG #image #multi
Matching Image with Multiple Local Features (YC, HZ, YG, XX, JG), pp. 519–522.
ICPRICPR-2010-Carneiro #automation #case study #comparative #design #image
A Comparative Study on the Use of an Ensemble of Feature Extractors for the Automatic Design of Local Image Descriptors (GC), pp. 3356–3359.
ICPRICPR-2010-ChenL #distance #recognition
Feature Space Hausdorff Distance for Face Recognition (SC, BCL), pp. 1465–1468.
ICPRICPR-2010-ColemanSG #architecture #feature model #using
Coarse Scale Feature Extraction Using the Spiral Architecture Structure (SAC, BWS, BG), pp. 2370–2373.
ICPRICPR-2010-CordellaSFMF #classification #performance
Combining Single Class Features for Improving Performance of a Two Stage Classifier (LPC, CDS, FF, CM, ASdF), pp. 4352–4355.
ICPRICPR-2010-DiamantiniGP #ranking
Feature Ranking Based on Decision Border (CD, AG, DP), pp. 609–612.
ICPRICPR-2010-DikmenH #canonical #classification #correlation
Improving Classification Accuracy by Comparing Local Features through Canonical Correlations (MD, TSH), pp. 4032–4035.
ICPRICPR-2010-DornaikaC #classification #detection #performance #using
Efficient Object Detection and Matching Using Feature Classification (FD, FC), pp. 3073–3076.
ICPRICPR-2010-DukkipatiYM #classification #feature model #modelling
Maximum Entropy Model Based Classification with Feature Selection (AD, AKY, MNM), pp. 565–568.
ICPRICPR-2010-DuYXGT #identification
Wavelet Domain Local Binary Pattern Features For Writer Identification (LD, XY, HX, ZG, YYT), pp. 3691–3694.
ICPRICPR-2010-EkbalSG #feature model #multi #optimisation #recognition #using
Feature Selection Using Multiobjective Optimization for Named Entity Recognition (AE, SS, CSG), pp. 1937–1940.
ICPRICPR-2010-Fan #recognition
Feature-Based Partially Occluded Object Recognition (NF), pp. 3001–3004.
ICPRICPR-2010-FangGC #estimation
Discriminant Feature Manifold for Facial Aging Estimation (HF, PWG, MC), pp. 593–596.
ICPRICPR-2010-GajsekSM #canonical #correlation #multi #recognition #using
Multi-modal Emotion Recognition Using Canonical Correlations and Acoustic Features (RG, VS, FM), pp. 4133–4136.
ICPRICPR-2010-GruberZWSH #optimisation
Optimization of Target Objects for Natural Feature Tracking (LG, SZ, DW, DS, TH), pp. 3607–3610.
ICPRICPR-2010-GuoC10a #constraints
Triangle-Constraint for Finding More Good Features (XG, XC), pp. 1393–1396.
ICPRICPR-2010-GuoZZ #multi #recognition
Feature Band Selection for Multispectral Palmprint Recognition (ZG, LZ, DZ), pp. 1136–1139.
ICPRICPR-2010-HafnerGLUVW #classification #image #using
Endoscopic Image Classification Using Edge-Based Features (MH, AG, ML, AU, AV, FW), pp. 2724–2727.
ICPRICPR-2010-HalderG #approach #documentation
Color Feature Based Approach for Determining Ink Age in Printed Documents (BH, UG), pp. 3212–3215.
ICPRICPR-2010-HanCR #categorisation #image #low level
Image Categorization by Learned Nonlinear Subspace of Combined Visual-Words and Low-Level Features (XHH, YWC, XR), pp. 3037–3040.
ICPRICPR-2010-HanerG #visual notation
Combining Foreground / Background Feature Points and Anisotropic Mean Shift For Enhanced Visual Object Tracking (SH, IYHG), pp. 3488–3491.
ICPRICPR-2010-HassanCG #documentation #image #kernel #retrieval #using
Document Image Retrieval Using Feature Combination in Kernel Space (EH, SC, MG), pp. 2009–2012.
ICPRICPR-2010-Hotta #classification #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-InoueSSF #feature model #modelling #using
High-Level Feature Extraction Using SIFT GMMs and Audio Models (NI, TS, KS, SF), pp. 3220–3223.
ICPRICPR-2010-IzadiS #automation #detection #image #segmentation #using
Automatic Building Detection in Aerial Images Using a Hierarchical Feature Based Image Segmentation (MI, PS), pp. 472–475.
ICPRICPR-2010-JeffersAH
Entropy of Feature Point-Based Retina Templates (JJ, AA, KJH), pp. 213–216.
ICPRICPR-2010-JiangWXD #classification #image
A New Biologically Inspired Feature for Scene Image Classification (AJ, CW, BX, RD), pp. 758–761.
ICPRICPR-2010-JungO #identification #image #web
Local Binary Pattern-Based Features for Text Identification of Web Images (IJ, ISO), pp. 4320–4323.
ICPRICPR-2010-KellyH #recognition #robust #speech
Auditory Features Revisited for Robust Speech Recognition (FK, NH), pp. 4456–4459.
ICPRICPR-2010-KimLL #approach #probability #segmentation
A Unified Probabilistic Approach to Feature Matching and Object Segmentation (THK, KML, SUL), pp. 464–467.
ICPRICPR-2010-KobayashiO10a #classification #image
Bag of Hierarchical Co-occurrence Features for Image Classification (TK, NO), pp. 3882–3885.
ICPRICPR-2010-KryszczukHS #orthogonal #predict #using
Direct Printability Prediction in VLSI Using Features from Orthogonal Transforms (KK, PH, RS), pp. 2764–2767.
ICPRICPR-2010-KuboPSS #retrieval #video
Video Retrieval Based on Tracked Features Quantization (HK, JP, HS, SS), pp. 3248–3251.
ICPRICPR-2010-LaiJYW #feature model
Sparse Local Discriminant Projections for Feature Extraction (ZL, ZJ, JY, WKW), pp. 926–929.
ICPRICPR-2010-Landesa-VazquezA #detection
The Role of Polarity in Haar-like Features for Face Detection (ILV, JLAC), pp. 412–415.
ICPRICPR-2010-LariosSSMLD #identification #kernel #random
Haar Random Forest Features and SVM Spatial Matching Kernel for Stonefly Species Identification (NL, BS, LGS, GMM, JL, TGD), pp. 2624–2627.
ICPRICPR-2010-LaunilaS #estimation #game studies
Contextual Features for Head Pose Estimation in Football Games (AL, JS), pp. 340–343.
ICPRICPR-2010-LeECA #case study #classification
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 #classification #linear #multi
A Discriminative and Heteroscedastic Linear Feature Transformation for Multiclass Classification (HSL, HMW, BC), pp. 690–693.
ICPRICPR-2010-LettnerS #robust
Combining Spectral and Spatial Features for Robust Foreground-Background Separation (ML, RS), pp. 1969–1972.
ICPRICPR-2010-LiuYZH #multi #recognition
Action Recognition by Multiple Features and Hyper-Sphere Multi-class SVM (JL, JY, YZ, XH), pp. 3744–3747.
ICPRICPR-2010-LuoFC #recognition
A MANOVA of Major Factors of RIU-LBP Feature for Face Recognition (JL, YF, QC), pp. 1028–1031.
ICPRICPR-2010-MatsukawaK #recognition #using
Action Recognition Using Three-Way Cross-Correlations Feature of Local Moton Attributes (TM, TK), pp. 1731–1734.
ICPRICPR-2010-MaTW #analysis #random #using
Nonlinear Blind Source Separation Using Slow Feature Analysis with Random Features (KM, QT, JW), pp. 830–833.
ICPRICPR-2010-MozaffariBA #classification #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-NgPS #automation #clustering #fuzzy
Automated Feature Weighting in Fuzzy Declustering-based Vector Quantization (TFN, TDP, CS), pp. 686–689.
ICPRICPR-2010-NguyenFP #detection #towards
Towards a Generic Feature-Selection Measure for Intrusion Detection (HTN, KF, SP), pp. 1529–1532.
ICPRICPR-2010-NishidaKOH #algorithm #using #visual notation
Visual Tracking Algorithm Using Pixel-Pair Feature (KN, TK, YO, MH), pp. 1808–1811.
ICPRICPR-2010-OGorman #analysis #latency #speech
Latency in Speech Feature Analysis for Telepresence Event Coding (LO), pp. 4464–4467.
ICPRICPR-2010-OReillyP #analysis #prototype #statistics
Prototype-Based Methodology for the Statistical Analysis of Local Features in Stereotypical Handwriting Tasks (CO, RP), pp. 1864–1867.
ICPRICPR-2010-PalenichkaLZ #difference #image
Outlier-Resistant Dissimilarity Measure for Feature-based Image Matching (RMP, AL, MBZ), pp. 846–849.
ICPRICPR-2010-ParisG #challenge #multi
Pyramidal Multi-level Features for the Robot Vision@ICPR 2010 Challenge (SP, HG), pp. 2949–2952.
ICPRICPR-2010-Parker #classification #empirical #feature model
An Empirical Study of Feature Extraction Methods for Audio Classification (CP), pp. 4593–4596.
ICPRICPR-2010-PaulaOBS #recognition #using
Forest Species Recognition Using Color-Based Features (PLdP, LSO, AdSBJ, RS), pp. 4178–4181.
ICPRICPR-2010-RahimBBP #analysis #sequence
Pelvic Organs Dynamic Feature Analysis for MRI Sequence Discrimination (MR, MEB, RB, NP), pp. 2496–2499.
ICPRICPR-2010-RahtuSH #random #using
Compressing Sparse Feature Vectors Using Random Ortho-Projections (ER, MS, JH), pp. 1397–1400.
ICPRICPR-2010-RoyM #using #video
Crossmodal Matching of Speakers Using Lip and Voice Features in Temporally Non-overlapping Audio and Video Streams (AR, SM), pp. 4504–4507.
ICPRICPR-2010-SakarK #analysis #canonical #correlation #feature model #hybrid
A Hybrid Method for Feature Selection Based on Mutual Information and Canonical Correlation Analysis (COS, OK), pp. 4360–4363.
ICPRICPR-2010-SakarKSG #clustering #feature model #predict
Prediction of Protein Sub-nuclear Location by Clustering mRMR Ensemble Feature Selection (COS, OK, HS, FG), pp. 2572–2575.
ICPRICPR-2010-SanromaAS #approach #graph #using
A Discrete Labelling Approach to Attributed Graph Matching Using SIFT Features (GS, RA, FS), pp. 954–957.
ICPRICPR-2010-SeverskyY #3d #detection #scalability #set
Scalable Cage-Driven Feature Detection and Shape Correspondence for 3D Point Sets (LMS, LY), pp. 3557–3560.
ICPRICPR-2010-ShahrokniGF #novel #performance #recognition
A Novel Shape Feature for Fast Region-Based Pedestrian Recognition (AS, DG, JMF), pp. 444–447.
ICPRICPR-2010-ShenYS #learning
Learning Discriminative Features Based on Distribution (JS, WY, CS), pp. 1401–1404.
ICPRICPR-2010-ShivakumaraPT #detection #video
New Wavelet and Color Features for Text Detection in Video (PS, TQP, CLT), pp. 3996–3999.
ICPRICPR-2010-ShivakumaraT #classification #novel #video
Novel Edge Features for Text Frame Classification in Video (PS, CLT), pp. 3191–3194.
ICPRICPR-2010-SoltanaACA #adaptation #algorithm #search-based #using
Adaptive Feature and Score Level Fusion Strategy Using Genetic Algorithms (WBS, MA, LC, CBA), pp. 4316–4319.
ICPRICPR-2010-SomolGP #algorithm #feature model #problem #set
The Problem of Fragile Feature Subset Preference in Feature Selection Methods and a Proposal of Algorithmic Workaround (PS, JG, PP), pp. 4396–4399.
ICPRICPR-2010-SongLLJ #detection #representation
A Discriminative Model for Object Representation and Detection via Sparse Features (XS, PL, LL, YJ), pp. 3077–3080.
ICPRICPR-2010-StottingerZKH #dataset #evaluation
FeEval A Dataset for Evaluation of Spatio-temporal Local Features (JS, SZ, RK, AH), pp. 499–502.
ICPRICPR-2010-StuhlsatzLZ #classification #feature model
Feature Extraction for Simple Classification (AS, JL, TZ), pp. 1525–1528.
ICPRICPR-2010-SuLY #recognition
Symbol Recognition Combining Vectorial and Pixel-Level Features for Line Drawings (FS, TL, RY), pp. 1892–1895.
ICPRICPR-2010-SunderR #image #retrieval
Iris Image Retrieval Based on Macro-features (MSS, AR), pp. 1318–1321.
ICPRICPR-2010-TasdemirC #detection #video
Motion Vector Based Features for Content Based Video Copy Detection (KT, AEÇ), pp. 3134–3137.
ICPRICPR-2010-TaWLBJ #recognition
Pairwise Features for Human Action Recognition (APT, CW, GL, AB, JMJ), pp. 3224–3227.
ICPRICPR-2010-Temerinac-OttKB #evaluation
Evaluation of a New Point Clouds Registration Method Based on Group Averaging Features (MTO, MK, HB), pp. 2452–2455.
ICPRICPR-2010-TorrentPLFSMP #approach #detection #using
Detecting Faint Compact Sources Using Local Features and a Boosting Approach (AT, MP, XL, JF, JRSS, JM, JMP), pp. 4613–4616.
ICPRICPR-2010-TumaIP #classification #kernel #set #using
Hydroacoustic Signal Classification Using Kernel Functions for Variable Feature Sets (MT, CI, MP), pp. 1011–1014.
ICPRICPR-2010-UchidaL #analysis #recognition
Analysis of Local Features for Handwritten Character Recognition (SU, ML), pp. 1945–1948.
ICPRICPR-2010-VachaH #invariant #recognition
Natural Material Recognition with Illumination Invariant Textural Features (PV, MH), pp. 858–861.
ICPRICPR-2010-WangB #automation #clustering #evaluation #fault #performance
Performance Evaluation of Automatic Feature Discovery Focused within Error Clusters (SYW, HSB), pp. 718–721.
ICPRICPR-2010-WangLS #documentation #identification #using
Noise Tolerant Script Identification of Printed Oriental and English Documents Using a Downgraded Pixel Density Feature (NW, LL, CYS), pp. 2037–2040.
ICPRICPR-2010-WanLJ #feature model
Feature Extraction Based on Class Mean Embedding (CME) (MW, ZL, ZJ), pp. 4174–4177.
ICPRICPR-2010-Weinman #recognition
Typographical Features for Scene Text Recognition (JJW), pp. 3987–3990.
ICPRICPR-2010-WongSML
Dynamic Amelioration of Resolution Mismatches for Local Feature Based Identity Inference (YW, CS, SM, BCL), pp. 1200–1203.
ICPRICPR-2010-WuLSZ #modelling #word
Integrating ILSR to Bag-of-Visual Words Model Based on Sparse Codes of SIFT Features Representations (LW, SL, WS, XZ), pp. 4283–4286.
ICPRICPR-2010-Xie #segmentation #set #using
Level Set Based Segmentation Using Local Feature Distribution (XX), pp. 2780–2783.
ICPRICPR-2010-XieLJ #adaptation #visual notation
Tracking Objects with Adaptive Feature Patches for PTZ Camera Visual Surveillance (YX, LL, YJ), pp. 1739–1742.
ICPRICPR-2010-XueJ #3d #recognition
A New Rotation Feature for Single Tri-axial Accelerometer Based 3D Spatial Handwritten Digit Recognition (YX, LJ), pp. 4218–4221.
ICPRICPR-2010-XuV
Binary Representations of Fingerprint Spectral Minutiae Features (HX, RNJV), pp. 1212–1216.
ICPRICPR-2010-YamakoshiHOKSSIYSM
Implicit Feature-Based Alignment System for Radiotherapy (RY, KH, HO, HK, KS, HS, YI, TY, DS, MM), pp. 2286–2289.
ICPRICPR-2010-YangK #feature model #fourier #performance
Fast Polar and Spherical Fourier Descriptors for Feature Extraction (ZY, SiK), pp. 975–978.
ICPRICPR-2010-YangLC
Bag of Features Tracking (FY, HL, YWC), pp. 153–156.
ICPRICPR-2010-YangZZZ #feature model #novel #recognition #representation
Monogenic Binary Pattern (MBP): A Novel Feature Extraction and Representation Model for Face Recognition (MY, LZ, LZ, DZ), pp. 2680–2683.
ICPRICPR-2010-Yildiz #feature model
Feature Extraction from Discrete Attributes (OTY), pp. 3915–3918.
ICPRICPR-2010-YoonK #recognition #using
Human Action Recognition Using Segmented Skeletal Features (SMY, AK), pp. 3740–3743.
ICPRICPR-2010-ZhangXL #detection #video
Extracting Key Sub-trajectory Features for Supervised Tactic Detection in Sports Video (YZ, CX, HL), pp. 125–128.
ICPRICPR-2010-ZhangXW #data transformation #detection
Data Transformation of the Histogram Feature in Object Detection (RZ, BX, CW), pp. 2893–2896.
ICPRICPR-2010-ZhaoGZ #evaluation #micropattern #performance #recognition #representation
Performance Evaluation of Micropattern Representation on Gabor Features for Face Recognition (SZ, YG, BZ), pp. 1273–1276.
ICPRICPR-2010-ZhaoHDC #3d #automation #feature model #recognition #statistics
Automatic 3D Facial Expression Recognition Based on a Bayesian Belief Net and a Statistical Facial Feature Model (XZ, DH, ED, LC), pp. 3724–3727.
ICPRICPR-2010-ZhaoLZZ #parallel
Parallel versus Hierarchical Fusion of Extended Fingerprint Features (QZ, FL, LZ, DZ), pp. 1132–1135.
ICPRICPR-2010-ZhaoWSS #feature model #process #recognition
Motif Discovery and Feature Selection for CRF-based Activity Recognition (LZ, XW, GS, RS), pp. 3826–3829.
ICPRICPR-2010-ZwengK #behaviour #image #multi #recognition #sequence #using
Unexpected Human Behavior Recognition in Image Sequences Using Multiple Features (AZ, MK), pp. 368–371.
KDDKDD-2010-CaiZH #clustering #feature model #multi
Unsupervised feature selection for multi-cluster data (DC, CZ, XH), pp. 333–342.
KDDKDD-2010-KongY #classification #feature model #graph
Semi-supervised feature selection for graph classification (XK, PSY), pp. 793–802.
KDDKDD-2010-LiAZ #mining
Mining positive and negative patterns for relevance feature discovery (YL, AA, NZ), pp. 753–762.
KDDKDD-2010-YangO #feature model #predict #probability #using
Feature selection for support vector regression using probabilistic prediction (JBY, CJO), pp. 343–352.
KDDKDD-2010-YuHW #clustering #documentation #feature model #process
Document clustering via dirichlet process mixture model with feature selection (GY, RzH, ZW), pp. 763–772.
KDDKDD-2010-ZhuLX #feature model #incremental #learning #markov #named #performance #random
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields (JZ, NL, EPX), pp. 303–312.
KDIRKDIR-2010-NcirEB #clustering #kernel
Kernel Overlapping K-Means for Clustering in Feature Space (CEBN, NE, PB), pp. 250–255.
KDIRKDIR-2010-PalmeriniRMCV #feature model
Feature Selection for the Instrumented Timed Up and Go in Parkinson’s Disease (LP, LR, SM, LC, FV), pp. 95–99.
KDIRKDIR-2010-SiebersS #feature model
Interleaving Forward Backward Feature Selection (MS, US), pp. 454–457.
KEODKEOD-2010-ReinosoOGH #approach #statistics #wiki
A Statistical Approach to the Impact of Featured Articles in Wikipedia (AJR, FO, JMGB, IH), pp. 420–423.
KRKR-2010-Poole #logic #semantics #towards
Towards a Logic of Feature-Based Semantic Science Theories (DP).
SEKESEKE-2010-Abu-MatarGKE #architecture #feature model #modelling #variability
Feature Modeling for Service Variability Management in Service-Oriented Architectures (MAM, HG, MK, AME), pp. 468–473.
SEKESEKE-2010-HirveMSV
Feature based Structuring and Composing of SDLC Artifacts (NH, TM, US, RV), pp. 583–586.
SEKESEKE-2010-WangKG #classification #feature model #quality
Ensemble Feature Selection Technique for Software Quality Classification (HW, TMK, KG), pp. 215–220.
SEKESEKE-2010-ZhangYW #question
Absent features or missing values? (WZ, YY, QW), pp. 6–11.
SIGIRSIGIR-2010-GopalY #classification #multi
Multilabel classification with meta-level features (SG, YY), pp. 315–322.
SIGIRSIGIR-2010-WangDL #comprehension #documentation #matrix #set
Feature subset non-negative matrix factorization and its applications to document understanding (DW, CHQD, TL), pp. 805–806.
ECMFAECMFA-2010-AcherCLF #composition #feature model
Comparing Approaches to Implement Feature Model Composition (MA, PC, PL, RBF), pp. 3–19.
MODELSMoDELS-v1-2010-WangXHZZM #approach #consistency #feature model #modelling
A Dynamic-Priority Based Approach to Fixing Inconsistent Feature Models (BW, YX, ZH, HZ, WZ, HM), pp. 181–195.
MODELSMoDELS-v2-2010-DenkerRGN #modelling #runtime
Modeling Features at Runtime (MD, JR, OG, ON), pp. 138–152.
GPCEGPCE-2010-SchulzeAK #feature model #product line
Code clones in feature-oriented software product lines (SS, SA, CK), pp. 103–112.
RERE-2010-StoiberFJG #product line #refactoring #requirements #specification #weaving
Feature Unweaving: Refactoring Software Requirements Specifications into Software Product Lines (RS, SF, MJ, MG), pp. 403–404.
REFSQREFSQ-2010-HubauxHSD #multi #towards
Towards Multi-view Feature-Based Configuration (AH, PH, PYS, DD), pp. 106–112.
SACSAC-2010-AthanasiadisFNS #3d #geometry #optimisation
Feature-based 3D morphing based on geometrically constrained sphere mapping optimization (TA, IF, CN, VS), pp. 1258–1265.
SACSAC-2010-BaccianellaES #feature model
Feature selection for ordinal regression (SB, AE, FS), pp. 1748–1754.
SACSAC-2010-BaeAVNB #algorithm #performance #search-based
Convex onion peeling genetic algorithm: an efficient solution to map labeling of point-feature (WDB, SA, PV, SN, KYB), pp. 892–899.
SACSAC-2010-EbraertDMJ #feature model
Intensional changes: modularizing crosscutting features (PE, TD, TM, DJ), pp. 2176–2182.
SACSAC-2010-Nakajima #automation #diagrams #feature model
Semi-automated diagnosis of FODA feature diagram (SN), pp. 2191–2197.
SACSAC-2010-RiosBKO #documentation #evaluation #set #word
Evaluation of different feature sets in an OCR free method for word spotting in printed documents (IR, AdSBJ, ALK, LSO), pp. 52–56.
SACSAC-2010-RoyM #verification #visual notation
Visual processing-inspired fern-audio features for noise-robust speaker verification (AR, SM), pp. 1491–1495.
SACSAC-2010-SillaKK #automation #classification #hybrid #music
Improving automatic music genre classification with hybrid content-based feature vectors (CNSJ, ALK, CAAK), pp. 1702–1707.
SACSAC-2010-SmithH #documentation #image #retrieval #using
Document retrieval using image features (DS, RH), pp. 47–51.
SACSAC-2010-Sobernig #feature model #interactive #network
Feature interaction networks (SS), pp. 2360–2364.
FSEFSE-2010-Elkhodary #adaptation #approach #feature model #self
A learning-based approach for engineering feature-oriented self-adaptive software systems (AME), pp. 345–348.
ICSEICSE-2010-SavageRP #feature model #named
FLAT3: feature location and textual tracing tool (TS, MR, DP), pp. 255–258.
ICSEICSE-2010-Shaker #feature model #modelling #requirements
Feature-oriented requirements modelling (PS), pp. 365–368.
SLESLE-2010-BakCW #metamodelling
Feature and Meta-Models in Clafer: Mixed, Specialized, and Coupled (KB, KC, AW), pp. 102–122.
SLESLE-2010-HubauxBHMH #case study #feature model #industrial #modelling
Evaluating a Textual Feature Modelling Language: Four Industrial Case Studies (AH, QB, HH, RM, PH), pp. 337–356.
PLEASEPLEASE-2010-BotterweckPDPK #evolution #named #product line
EvoFM: feature-driven planning of product-line evolution (GB, AP, DD, AP, SK), pp. 24–31.
PLEASEPLEASE-2010-KammullerRR #higher-order #variability
Feature link propagation across variability representations with Isabelle/HOL (FK, AR, MOR), pp. 48–53.
SPLCSPLC-2010-BagheriAGS #process
Stratified Analytic Hierarchy Process: Prioritization and Selection of Software Features (EB, MA, DG, SS), pp. 300–315.
SPLCSPLC-2010-BagheriNRG #configuration management #feature model #modelling #product line #requirements
Configuring Software Product Line Feature Models Based on Stakeholders’ Soft and Hard Requirements (EB, TDN, AR, DG), pp. 16–31.
SPLCSPLC-2010-BergerSLCW #product line #scalability
Feature-to-Code Mapping in Two Large Product Lines (TB, SS, RL, KC, AW), pp. 498–499.
SPLCSPLC-2010-CosmoZ #dependence #diagrams #feature model
Feature Diagrams as Package Dependencies (RDC, SZ), pp. 476–480.
SPLCSPLC-2010-DaoK #approach #component #problem #reuse
Mapping Features to Reusable Components: A Problem Frames-Based Approach (TMD, KCK), pp. 377–392.
SPLCSPLC-2010-GhanamM #execution #feature model #modelling #testing #using
Linking Feature Models to Code Artifacts Using Executable Acceptance Tests (YG, FM), pp. 211–225.
SPLCSPLC-2010-GilKM #constraints #diagrams #feature model #modelling
Sans Constraints? Feature Diagrams vs. Feature Models (JYG, SKD, IM), pp. 271–285.
SPLCSPLC-2010-GuoW #consistency #evolution #feature model #modelling #towards
Towards Consistent Evolution of Feature Models (JG, YW), pp. 451–455.
SPLCSPLC-2010-KaratasOD #constraints #feature model #finite #logic programming #modelling
Mapping Extended Feature Models to Constraint Logic Programming over Finite Domains (ASK, HO, AHD), pp. 286–299.
SPLCSPLC-2010-LeeK #feature model
Usage Context as Key Driver for Feature Selection (KL, KCK), pp. 32–46.
SPLCSPLC-2010-Nakajima #automation #diagrams #encoding #feature model
Non-clausal Encoding of Feature Diagram for Automated Diagnosis (SN), pp. 420–424.
SPLCSPLC-2010-YoshimuraAF #constraints #feature model #identification #mining
A Method to Identify Feature Constraints Based on Feature Selections Mining (KY, YA, TF), pp. 425–429.
SPLCSPLC-2010-ZhangJ #approach #feature model #hybrid #programming
A Hybrid Approach to Feature-Oriented Programming in XVCL (HZ, SJ), pp. 440–445.
ICSTICST-2010-SeguraHBR #analysis #approach #automation #feature model #generative #modelling #testing
Automated Test Data Generation on the Analyses of Feature Models: A Metamorphic Testing Approach (SS, RMH, DB, ARC), pp. 35–44.
ICTSSICTSS-2010-LamanchaU #generative #product line #testing #using
Testing Product Generation in Software Product Lines Using Pairwise for Features Coverage (BPL, MPU), pp. 111–125.
WICSA-ECSAWICSA-ECSA-2009-PerovichRB #architecture #feature model #product line
Feature model to product architectures: Applying MDE to Software Product Lines (DP, POR, MCB), pp. 201–210.
ASEASE-2009-ShivajiWAK #debugging #predict
Reducing Features to Improve Bug Prediction (SS, EJWJ, RA, SK), pp. 600–604.
ICDARICDAR-2009-AgrawalD09a #approach #segmentation
Voronoi++: A Dynamic Page Segmentation Approach Based on Voronoi and Docstrum Features (MA, DSD), pp. 1011–1015.
ICDARICDAR-2009-AssabieB #recognition #word
HMM-Based Handwritten Amharic Word Recognition with Feature Concatenation (YA, JB), pp. 961–965.
ICDARICDAR-2009-BenjelilKMA #identification
Arabic and Latin Script Identification in Printed and Handwritten Types Based on Steerable Pyramid Features (MB, SK, RM, AMA), pp. 591–595.
ICDARICDAR-2009-ChouaibVCT #documentation #feature model
Generic Feature Selection and Document Processing (HC, NV, FC, ST), pp. 356–360.
ICDARICDAR-2009-DiemS #recognition #using
Recognition of Degraded Handwritten Characters Using Local Features (MD, RS), pp. 221–225.
ICDARICDAR-2009-EmmanouilidisBP #classification #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-FornesLSB #identification #music #on the
On the Use of Textural Features for Writer Identification in Old Handwritten Music Scores (AF, JL, GS, HB), pp. 996–1000.
ICDARICDAR-2009-HaboubiMEA #invariant #set
Invariant Primitives for Handwritten Arabic Script: A Contrastive Study of Four Feature Sets (SH, SM, NE, HEA), pp. 691–697.
ICDARICDAR-2009-HamdaniAKA #multi #online #recognition #using
Combining Multiple HMMs Using On-line and Off-line Features for Off-line Arabic Handwriting Recognition (MH, HEA, MK, AMA), pp. 201–205.
ICDARICDAR-2009-IbrahimKKAG #analysis #dependence #online #using #verification
On-Line Signature Verification: Directional Analysis of a Signature Using Weighted Relative Angle Partitions for Exploitation of Inter-Feature Dependencies (MTI, MJK, MAK, KSA, LG), pp. 41–45.
ICDARICDAR-2009-KukC #documentation #image
Feature Based Binarization of Document Images Degraded by Uneven Light Condition (JGK, NIC), pp. 748–752.
ICDARICDAR-2009-LecerfC #documentation #feature model #scalability
Scalable Feature Extraction from Noisy Documents (LL, BC), pp. 361–365.
ICDARICDAR-2009-LiFWL #documentation #image #retrieval #sequence
Document Image Retrieval with Local Feature Sequences (JL, ZGF, YW, NL), pp. 346–350.
ICDARICDAR-2009-LiST #identification #independence #online
Hierarchical Shape Primitive Features for Online Text-independent Writer Identification (BL, ZS, TT), pp. 986–990.
ICDARICDAR-2009-MaHS #case study #design #markov #modelling #online #recognition
A Study of Feature Design for Online Handwritten Chinese Character Recognition Based on Continuous-Density Hidden Markov Models (LM, QH, YS), pp. 526–530.
ICDARICDAR-2009-NguyenBL #problem #verification
Global Features for the Off-Line Signature Verification Problem (VN, MB, GL), pp. 1300–1304.
ICDARICDAR-2009-PalWK #case study #classification #comparative #recognition #using
Comparative Study of Devnagari Handwritten Character Recognition Using Different Feature and Classifiers (UP, TW, FK), pp. 1111–1115.
ICDARICDAR-2009-SchenkKR #online #question #recognition
Selecting Features in On-Line Handwritten Whiteboard Note Recognition: SFS or SFFS? (JS, MK, GR), pp. 1251–1254.
ICDARICDAR-2009-SiddiqiV #recognition #set
A Set of Chain Code Based Features for Writer Recognition (IS, NV), pp. 981–985.
ICDARICDAR-2009-TerasawaT #documentation #image #word
Slit Style HOG Feature for Document Image Word Spotting (KT, YT), pp. 116–120.
ICDARICDAR-2009-VamvakasGP #classification #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-WakabayashiPKM #feature model #recognition
F-ratio Based Weighted Feature Extraction for Similar Shape Character Recognition (TW, UP, FK, YM), pp. 196–200.
ICDARICDAR-2009-WangBA #automation #documentation #using
Document Content Extraction Using Automatically Discovered Features (SYW, HSB, CA), pp. 1076–1080.
ICDARICDAR-2009-WangC #bound #detection #documentation #image
Logo Detection in Document Images Based on Boundary Extension of Feature Rectangles (HW, YC), pp. 1335–1339.
ICDARICDAR-2009-WangHL #verification
A New Block Partitioned Text Feature for Text Verification (XW, LH, CL), pp. 366–370.
ICDARICDAR-2009-ZhangJDG #named #novel #recognition
Character-SIFT: A Novel Feature for Offline Handwritten Chinese Character Recognition (ZZ, LJ, KD, XG), pp. 763–767.
ICDARICDAR-2009-ZhuSMHN #classification #feature model
Separate Chinese Character and English Character by Cascade Classifier and Feature Selection (YZ, JS, AM, YH, SN), pp. 1191–1195.
FASEFASE-2009-NguyenNPAN #clone detection #detection #feature model #performance
Accurate and Efficient Structural Characteristic Feature Extraction for Clone Detection (HAN, TTN, NHP, JMAK, TNN), pp. 440–455.
ICPCICPC-2009-EdwardsWSG #feature model
Instrumenting time-sensitive software for feature location (DE, NW, SS, EG), pp. 130–137.
ICPCICPC-2009-KimSW #configuration management #named
Kenyon-web: Reconfigurable web-based feature extractor (SK, SS, EJWJ), pp. 287–288.
ICPCICPC-2009-RevelleP #case study #feature model
An exploratory study on assessing feature location techniques (MR, DP), pp. 218–222.
ICSMEICSM-2009-GeetD #case study #cobol #experience #feature model
Feature location in COBOL mainframe systems: An experience report (JVG, SD), pp. 361–370.
ICSMEICSM-2009-HouW #case study #eclipse #evolution
Analyzing the evolution of user-visible features: A case study with Eclipse (DH, YW), pp. 479–482.
WCREWCRE-1999-Revelle99a #maintenance
Supporting Feature-Level Software Maintenance (MR), pp. 287–290.
WCREWCRE-1999-YangPZ99a #concept analysis #data access #feature model #multi #semantics #using
Domain Feature Model Recovery from Multiple Applications Using Data Access Semantics and Formal Concept Analysis (YY, XP, WZ), pp. 215–224.
HCIHCD-2009-KrohnKH #approach #design #development #web
User-Centered Design Meets Feature-Driven Development: An Integrating Approach for Developing the Web Application myPIM (TK, MCK, MH), pp. 739–748.
HCIHCI-NIMT-2009-MurakamiK #classification #music
Study of Feature Values for Subjective Classification of Music (MM, TK), pp. 701–709.
HCIHCI-NT-2009-AsteriadisKK #feature model #human-computer
Feature Extraction and Selection for Inferring User Engagement in an HCI Environment (SA, KK, SDK), pp. 22–29.
HCIHIMI-DIE-2009-SrinivasSPK #classification #feature model #performance #using
Efficient Text Classification Using Best Feature Selection and Combination of Methods (MS, KPS, EVP, SAK), pp. 437–446.
HCIHIMI-II-2009-KimMPH #performance #using #visualisation
Efficient Annotation Visualization Using Distinctive Features (SKK, SHM, JP, SYH), pp. 295–303.
HCIHIMI-II-2009-RheeKKLC #communication
Expanding SNS Features with CE Devices: Space, Profile, Communication (YR, HK, YK, JL, IC), pp. 458–467.
HCIOCSC-2009-ChaLHK #evaluation #using
User Reputation Evaluation Using Co-occurrence Feature and Collective Intelligence (JWC, HwL, YSH, LK), pp. 305–311.
HCIOCSC-2009-LauK #bibliography #community #online #perspective #social
Social Features in Online Communities for Healthcare Consumers — A Review (AYSL, TMYK), pp. 682–689.
ICEISICEIS-AIDSS-2009-ZhengZLL #case study #classification #image #multi
Study on Image Classification based on SVM and the Fusion of Multiple Features (DZ, TZ, SL, YL), pp. 80–84.
CIKMCIKM-2009-FeiH #graph #kernel
L2 norm regularized feature kernel regression for graph data (HF, JH), pp. 593–600.
CIKMCIKM-2009-FernandezL #retrieval #using
Using opinion-based features to boost sentence retrieval (RTF, DEL), pp. 1617–1620.
CIKMCIKM-2009-FigueiredoBPAGFMC #quality #web
Evidence of quality of textual features on the web 2.0 (FF, FB, HP, JMA, MAG, DFdO, ESdM, MC), pp. 909–918.
CIKMCIKM-2009-GuoZGZS #categorisation #multi #semantics
Product feature categorization with multilevel latent semantic association (HG, HZ, ZG, XZ, ZS), pp. 1087–1096.
CIKMCIKM-2009-LiaoM #documentation #re-engineering
Feature engineering on event-centric surrogate documents to improve search results (WL, IM), pp. 1629–1632.
CIKMCIKM-2009-MartineauFJP #classification #difference #problem #using #word
Improving binary classification on text problems using differential word features (JM, TF, AJ, SP), pp. 2019–2024.
CIKMCIKM-2009-PanCASD #feature model #ranking #using
Feature selection for ranking using boosted trees (FP, TC, DA, FS, GD), pp. 2025–2028.
CIKMCIKM-2009-XuFZH #feature model #orthogonal #using
To obtain orthogonal feature extraction using training data selection (YX, SF, JZ, OH), pp. 1819–1822.
CIKMCIKM-2009-YangXBHSY #case study #cumulative #generative #information retrieval #social #using
A study of information retrieval on accumulative social descriptions using the generation features (LY, SX, SB, DH, ZS, YY), pp. 721–730.
CIKMCIKM-2009-YuOH #performance #ranking
Efficient feature weighting methods for ranking (HY, JO, WSH), pp. 1157–1166.
CIKMCIKM-2009-ZhangXSYD #evaluation #learning #named
ROSE: retail outlet site evaluation by learning with both sample and feature preference (BZ, MX, JYS, WJY, JD), pp. 1397–1404.
ECIRECIR-2009-BidokiT #documentation
Combination of Documents Features Based on Simulated Click-through Data (AMZB, JAT), pp. 538–545.
ECIRECIR-2009-EsuliS09a #classification #encoding
Encoding Ordinal Features into Binary Features for Text Classification (AE, FS), pp. 771–775.
ECIRECIR-2009-HalveyPHVHGJ #case study #difference #low level #metric #retrieval #using #video
Diversity, Assortment, Dissimilarity, Variety: A Study of Diversity Measures Using Low Level Features for Video Retrieval (MH, PP, DH, RV, FH, AG, JMJ), pp. 126–137.
ECIRECIR-2009-PengO #independence #information retrieval #web
Selective Application of Query-Independent Features in Web Information Retrieval (JP, IO), pp. 375–387.
ECIRECIR-2009-TsagkiasLR #predict
Exploiting Surface Features for the Prediction of Podcast Preference (MT, ML, MdR), pp. 473–484.
ICMLICML-2009-BoutilierRV #elicitation #interactive #online #optimisation
Online feature elicitation in interactive optimization (CB, KR, PV), pp. 73–80.
ICMLICML-2009-DiukLL #adaptation #feature model #learning #problem
The adaptive k-meteorologists problem and its application to structure learning and feature selection in reinforcement learning (CD, LL, BRL), pp. 249–256.
ICMLICML-2009-HelleputteD #feature model #linear #modelling
Partially supervised feature selection with regularized linear models (TH, PD), pp. 409–416.
ICMLICML-2009-KolterN09a #difference #feature model #learning
Regularization and feature selection in least-squares temporal difference learning (JZK, AYN), pp. 521–528.
ICMLICML-2009-KuzelkaZ #relational
Block-wise construction of acyclic relational features with monotone irreducibility and relevancy properties (OK, FZ), pp. 569–576.
ICMLICML-2009-WeinbergerDLSA #learning #multi #scalability
Feature hashing for large scale multitask learning (KQW, AD, JL, AJS, JA), pp. 1113–1120.
ICMLICML-2009-XuJYLK #feature model
Non-monotonic feature selection (ZX, RJ, JY, MRL, IK), pp. 1145–1152.
ICMLICML-2009-YuanH #feature model #learning #robust
Robust feature extraction via information theoretic learning (XY, BGH), pp. 1193–1200.
KDDKDD-2009-FormanSR #classification #linear
Feature shaping for linear SVM classifiers (GF, MS, SR), pp. 299–308.
KDDKDD-2009-JiYLZKY #interactive #using
Drosophila gene expression pattern annotation using sparse features and term-term interactions (SJ, LY, YXL, ZHZ, SK, JY), pp. 407–416.
KDDKDD-2009-LoscalzoYD #feature model
Consensus group stable feature selection (SL, LY, CHQD), pp. 567–576.
KDIRKDIR-2009-SilvestreCF #category theory #clustering #modelling
Selecting Categorical Features in Model-based Clustering (CMVS, MMGSC, MATF), pp. 303–306.
MLDMMLDM-2009-JingWYX #categorisation #feature model #framework
A General Framework of Feature Selection for Text Categorization (HJ, BW, YY, YX), pp. 647–662.
MLDMMLDM-2009-LiuYZZZL #classification #scalability
A Large Margin Classifier with Additional Features (XL, JY, EZ, GZ, YZ, ML), pp. 82–95.
MLDMMLDM-2009-SeredinKM #machine learning #order #set
Selection of Subsets of Ordered Features in Machine Learning (OS, AK, VM), pp. 16–28.
RecSysRecSys-2009-BaoBT #recommendation
Stacking recommendation engines with additional meta-features (XB, LB, RT), pp. 109–116.
RecSysRecSys-2009-BoutilierRV #elicitation
Preference elicitation with subjective features (CB, KR, PV), pp. 341–344.
SEKESEKE-2009-LinWK #algorithm #feature model #hybrid #novel
A Novel Hybrid Search Algorithm for Feature Selection (PL, HW, TMK), pp. 81–86.
SEKESEKE-2009-Nakajima #diagrams #feature model
Constructing FODA Feature Diagrams with a GUI-based Tool (SN), pp. 20–25.
SIGIRSIGIR-2009-AmbaiY #clustering #image #multi #ranking #set #visual notation
Multiclass VisualRank: image ranking method in clustered subsets based on visual features (MA, YY), pp. 732–733.
SIGIRSIGIR-2009-KellyGB #comparison #interactive #query
A comparison of query and term suggestion features for interactive searching (DK, KG, EWB), pp. 371–378.
SIGIRSIGIR-2009-Liu09a #information retrieval #personalisation #topic #using
Personalizing information retrieval using task features, topic knowledge, and task product (JL), p. 855.
SIGIRSIGIR-2009-PunithaJG #automation #feature model #multi #query #retrieval #topic #using #video
Topic prerogative feature selection using multiple query examples for automatic video retrieval (PP, JMJ, AG), pp. 804–805.
SIGIRSIGIR-2009-YangC #automation #feature model #induction #taxonomy
Feature selection for automatic taxonomy induction (HY, JC), pp. 684–685.
GPCEGPCE-2009-KastnerAK #refactoring
A model of refactoring physically and virtually separated features (CK, SA, MK), pp. 157–166.
GPCEGPCE-2009-KuhlemannBK #composition
Safe composition of non-monotonic features (MK, DSB, CK), pp. 177–186.
GPCEGPCE-2009-SanenTJ #approach #feature model #interactive #problem
Mapping problem-space to solution-space features: a feature interaction approach (FS, ET, WJ), pp. 167–176.
PPDPPPDP-2009-CodishGS #declarative #encoding #satisfiability
A declarative encoding of telecommunications feature subscription in SAT (MC, SG, PJS), pp. 255–266.
RERE-2009-ClassenHH #analysis #feature model #workflow
Analysis of Feature Configuration Workflows (AC, AH, PH), pp. 381–382.
RERE-2009-KauppinenSLKTD #development
From Feature Development to Customer Value Creation (MK, JS, LL, MK, HT, AMD), pp. 275–280.
RERE-2009-SalinesiRDM #classification #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.
RERE-2009-WaldmannJ #feature model #perspective #requirements #reuse
Feature-oriented Requirements Satisfy Needs for Reuse and Systems View (BW, PJ), pp. 329–334.
RERE-2009-WangZZJM #approach #case study #feature model #modelling
A Use Case Based Approach to Feature Models’ Construction (BW, WZ, HZ, ZJ, HM), pp. 121–130.
RERE-2009-WnukRK #comprehension #industrial #scalability #visualisation #what
What Happened to Our Features? Visualization and Understanding of Scope Change Dynamics in a Large-Scale Industrial Setting (KW, BR, LK), pp. 89–98.
SACSAC-2009-EbraertVV #flexibility #reuse
Flexible features: making feature modules more reusable (PE, JV, YV), pp. 1963–1970.
SACSAC-2009-LeS #concept #detection #performance #visual notation
Efficient concept detection by fusing simple visual features (DDL, SS), pp. 1839–1840.
SACSAC-2009-LiuDSYH #algorithm #classification #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-MarquesF #documentation #using
Reconstructing strip-shredded documents using color as feature matching (MAOM, COAF), pp. 893–894.
SACSAC-2009-ZaidKT #feature model #modelling #semantics #web
Applying semantic web technology to feature modeling (LAZ, FK, ODT), pp. 1252–1256.
SACSAC-2009-ZhangCCW #clustering #image #visual notation
Revealing common sources of image spam by unsupervised clustering with visual features (CZ, WbC, XC, GW), pp. 891–892.
ICSEICSE-2009-KastnerTSFLWA #development #feature model #framework #named
FeatureIDE: A tool framework for feature-oriented software development (CK, TT, GS, JF, TL, FW, SA), pp. 611–614.
ICSEICSE-2009-ThumBK #feature model #modelling #reasoning
Reasoning about edits to feature models (TT, DSB, CK), pp. 254–264.
SLESLE-2009-AcherCLF #feature model #modelling
Composing Feature Models (MA, PC, PL, RBF), pp. 62–81.
SPLCSPLC-2009-Fernandez-AmorosGS #diagrams #feature model #modelling #product line
Inferring information from feature diagrams to product line economic models (DFA, RHG, JACS), pp. 41–50.
SPLCSPLC-2009-HartmannTM #feature model #independence #modelling
Supplier independent feature modelling (HH, TT, AAJM), pp. 191–200.
SPLCSPLC-2009-HubauxCH #feature model #formal method #modelling #workflow
Formal modelling of feature configuration workflows (AH, AC, PH), pp. 221–230.
SPLCSPLC-2009-KastnerARRBS #analysis #case study #on the #problem
On the impact of the optional feature problem: analysis and case studies (CK, SA, SSuR, MR, DSB, GS), pp. 181–190.
SPLCSPLC-2009-MendoncaWC #analysis #feature model #modelling #satisfiability
SAT-based analysis of feature models is easy (MM, AW, KC), pp. 231–240.
SPLCSPLC-2009-TunBCHH #approach #feature model #requirements
Relating requirements and feature configurations: a systematic approach (TTT, QB, AC, AH, PH), pp. 201–210.
SPLCSPLC-2009-WestonCR #composition #feature model #framework #modelling #natural language #requirements #semantics
A framework for constructing semantically composable feature models from natural language requirements (NW, RC, AR), pp. 211–220.
SPLCSPLC-2009-WhiteDSB #automation #feature model #multi #problem #reasoning
Automated reasoning for multi-step feature model configuration problems (JW, BD, DCS, DB), pp. 11–20.
CCCC-2009-KnightsMSMD #hardware #optimisation
Blind Optimization for Exploiting Hardware Features (DK, TM, PFS, MCM, AD), pp. 251–265.
CGOCGO-2009-LeatherBO #automation #compilation #generative #machine learning #optimisation
Automatic Feature Generation for Machine Learning Based Optimizing Compilation (HL, EVB, MFPO), pp. 81–91.
HPDCHPDC-2009-LiSDZ #parallel #performance #predict
Performance prediction based on hierarchy parallel features captured in multi-processing system (JL, FS, ND, QZ), pp. 63–64.
ECSAECSA-2008-DamaseviciusST #component #design #diagrams #feature model #generative #metaprogramming #ontology #using
Domain Ontology-Based Generative Component Design Using Feature Diagrams and Meta-programming Techniques (RD, VS, JT), pp. 338–341.
ASEASE-2008-Dominguez #detection #feature model #interactive
Feature Interaction Detection in the Automotive Domain (ALJD), pp. 521–524.
ASEASE-2008-GeW #feature model #framework #generative #modelling #named
Rhizome: A Feature Modeling and Generation Platform (GG, EJWJ), pp. 375–378.
CASECASE-2008-SunWHRW #case study #effectiveness #identification #monitoring #set
Identification of feature set for effective tool condition monitoring — a case study in titanium machining (JS, YSW, GSH, MR, ZW), pp. 273–278.
DATEDATE-2008-MucciVMGDGKSCC #adaptation #array #configuration management #implementation #parallel #pipes and filters
Implementation of Parallel LFSR-based Applications on an Adaptive DSP featuring a Pipelined Configurable Gate Array (CM, LV, IM, DG, AD, SG, JK, AS, LC, FC), pp. 1444–1449.
DRRDRR-2008-HottaF #recognition #synthesis
Line-touching character recognition based on dynamic reference feature synthesis (YH, KF), p. 68150.
HTHT-2008-BatemanGN #in the cloud #visual notation
Seeing things in the clouds: the effect of visual features on tag cloud selections (SB, CG, MAN), pp. 193–202.
FASEFASE-2008-ClassenHS #perspective #requirements #what
What’s in a Feature: A Requirements Engineering Perspective (AC, PH, PYS), pp. 16–30.
FASEFASE-2008-JanotaB #approach #architecture #formal method #modelling
Formal Approach to Integrating Feature and Architecture Models (MJ, GB), pp. 31–45.
CSMRCSMR-2008-AldekoaTMD #maintenance #product line
Quantifying Maintainability in Feature Oriented Product Lines (GA, ST, GSM, OD), pp. 243–247.
ICPCICPC-2008-BohnetVD #comprehension #execution
Locating and Understanding Features of Complex Software Systems by Synchronizing Time-, Collaboration- and Code-Focused Views on Execution Traces (JB, SV, JD), pp. 268–271.
ICPCICPC-2008-RohatgiHR #approach #dynamic analysis
An Approach for Mapping Features to Code Based on Static and Dynamic Analysis (AR, AHL, JR), pp. 236–241.
ICSMEICSM-2008-KothariBMS #algebra #development #on the #performance #using
On evaluating the efficiency of software feature development using algebraic manifolds (JK, DB, SM, AS), pp. 7–16.
WCREWCRE-2008-Ebraert #feature model #programming
First-Class Change Objects for Feature-Oriented Programming (PE), pp. 319–322.
WCREWCRE-2008-SobreiraM #analysis #comprehension #visual notation
A Visual Trace Analysis Tool for Understanding Feature Scattering (VS, MdAM), pp. 337–338.
SOFTVISSOFTVIS-2008-SensalireOT #maintenance #tool support #visualisation
Classifying desirable features of software visualization tools for corrective maintenance (MS, PO, ACT), pp. 87–90.
AdaEuropeAdaEurope-2008-Brosgol #ada #comparison #java #object-oriented
A Comparison of the Object-Oriented Features of Ada 2005 and JavaTM (BMB), pp. 115–129.
ICEISICEIS-AIDSS-2008-AccianiFMM #classification #feature model #search-based #statistics
Genetic Feature Selection and Statistical Classification of Voids in Concrete Structure (GA, GF, DM, DM), pp. 231–234.
CIKMCIKM-2008-ArnoldC #adaptation
Intra-document structural frequency features for semi-supervised domain adaptation (AA, WWC), pp. 1291–1300.
CIKMCIKM-2008-FeiH #classification #feature model #graph
Structure feature selection for graph classification (HF, JH), pp. 991–1000.
CIKMCIKM-2008-Forman #classification #representation #scalability
BNS feature scaling: an improved representation over tf-idf for svm text classification (GF), pp. 263–270.
CIKMCIKM-2008-FormanK #classification #feature model #performance
Extremely fast text feature extraction for classification and indexing (GF, EK), pp. 1221–1230.
CIKMCIKM-2008-LiuLNBMG #dataset #feature model #performance #preprocessor #realtime #scalability
Real-time data pre-processing technique for efficient feature extraction in large scale datasets (YL, LVL, RSN, KB, PM, CLG), pp. 981–990.
CIKMCIKM-2008-MiaoLD #integration #mining
An integration strategy for mining product features and opinions (QM, QL, RD), pp. 1369–1370.
CIKMCIKM-2008-PickensG #ad hoc #modelling #retrieval
Ranked feature fusion models for ad hoc retrieval (JP, GG), pp. 893–900.
CIKMCIKM-2008-ZhuSRH #documentation #modelling
Modeling document features for expert finding (JZ, DS, SMR, XH), pp. 1421–1422.
ICMLICML-2008-DekelS #learning
Learning to classify with missing and corrupted features (OD, OS), pp. 216–223.
ICMLICML-2008-LiangDK #compilation
Structure compilation: trading structure for features (PL, HDI, DK), pp. 592–599.
ICMLICML-2008-ParrLTPL #analysis #approximate #feature model #learning #linear #modelling
An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning (RP, LL, GT, CPW, MLL), pp. 752–759.
ICMLICML-2008-RaykarKBDR #automation #feature model #induction #learning #multi
Bayesian multiple instance learning: automatic feature selection and inductive transfer (VCR, BK, JB, MD, RBR), pp. 808–815.
ICMLICML-2008-SeldinT #category theory #classification #clustering #multi
Multi-classification by categorical features via clustering (YS, NT), pp. 920–927.
ICMLICML-2008-VincentLBM #robust
Extracting and composing robust features with denoising autoencoders (PV, HL, YB, PAM), pp. 1096–1103.
ICMLICML-2008-WangYQZ #analysis #component #composition #feature model
Dirichlet component analysis: feature extraction for compositional data (HYW, QY, HQ, HZ), pp. 1128–1135.
ICPRICPR-2008-BarratT #effectiveness #image #network #retrieval #semantics #using #visual notation
Visual features with semantic combination using Bayesian network for a more effective image retrieval (SB, ST), pp. 1–4.
ICPRICPR-2008-BazinKDV #image #using
Improvement of feature matching in catadioptric images using gyroscope data (JCB, IK, CD, PV), pp. 1–5.
ICPRICPR-2008-ChangFLI #clustering #detection #kernel #multi
Clustered Microcalcification detection based on a Multiple Kernel Support Vector Machine with Grouped Features (GF-SVM) (TTC, JF, HWL, HHSI), pp. 1–4.
ICPRICPR-2008-ChenSSL #image #recognition
Representative feature chain for single gallery image face recognition (SC, CS, SS, BCL), pp. 1–4.
ICPRICPR-2008-ChenWWM #detection #generative
GA based feature generation for training cascade object detector (QC, HW, TW, KM), pp. 1–4.
ICPRICPR-2008-ChouaibTTCV #algorithm #classification #feature model #search-based
Feature selection combining genetic algorithm and Adaboost classifiers (HC, ORT, ST, FC, NV), pp. 1–4.
ICPRICPR-2008-EngelC #invariant
Scale-invariant medial features based on gradient vector flow fields (DE, CC), pp. 1–4.
ICPRICPR-2008-FakihZ
Structure from Motion: Combining features correspondences and optical flow (AHF, JSZ), pp. 1–4.
ICPRICPR-2008-FuSHLT #image #kernel #learning #multi #set
Multiple kernel learning from sets of partially matching image features (SYF, GS, ZGH, ZzL, MT), pp. 1–4.
ICPRICPR-2008-GehrigS #recognition
Selecting relevant features for human motion recognition (DG, TS), pp. 1–4.
ICPRICPR-2008-GurS #detection #invariant
Non-Abelian invariant feature detection (YG, NAS), pp. 1–4.
ICPRICPR-2008-HajOGV #automation #robust
Automatic face and facial features initialization for robust and accurate tracking (MAH, JO, JG, JV), pp. 1–4.
ICPRICPR-2008-HanYJ #evaluation #online #using
Online feature evaluation for object tracking using Kalman Filter (ZH, QY, JJ), pp. 1–4.
ICPRICPR-2008-HeiseleR #recognition
Local shape features for object recognition (BH, CR), pp. 1–4.
ICPRICPR-2008-HidakaK #feature model #optimisation #using
Non-Neighboring Rectangular Feature selection using Particle Swarm Optimization (AH, TK), pp. 1–4.
ICPRICPR-2008-KatayamaUS #coordination #online #recognition #using
A new HMM for on-line character recognition using pen-direction and pen-coordinate features (YK, SU, HS), pp. 1–4.
ICPRICPR-2008-KazuiMMF #detection #matrix #using
Incoherent motion detection using a time-series Gram matrix feature (MK, MM, SM, HF), pp. 1–5.
ICPRICPR-2008-Kong #evaluation #recognition
An evaluation of Gabor orientation as a feature for face recognition (AK), pp. 1–4.
ICPRICPR-2008-KrizekKH #algorithm #feature model
Feature condensing algorithm for feature selection (PK, JK, VH), pp. 1–4.
ICPRICPR-2008-LangerK #approach #detection #image #realtime #robust
A new hierarchical approach in robust real-time image feature detection and matching (ML, KDK), pp. 1–4.
ICPRICPR-2008-LiCSCG #image
Hallucinating facial images and features (BL, HC, SS, XC, WG), pp. 1–4.
ICPRICPR-2008-LiDM #feature model #learning #locality #using
Localized feature selection for Gaussian mixtures using variational learning (YL, MD, YM), pp. 1–4.
ICPRICPR-2008-LillholmG #image #novel #recognition
Novel image feature alphabets for object recognition (ML, LDG), pp. 1–4.
ICPRICPR-2008-LiLS #feature model #invariant #recognition
Redundant DWT based translation invariant wavelet feature extraction for face recognition (DL, HL, ZS), pp. 1–4.
ICPRICPR-2008-LiuS08a #detection #robust #using
Robust outdoor text detection using text intensity and shape features (ZL, SS), pp. 1–4.
ICPRICPR-2008-Lopez-Garcia #recognition
SIFT features for object recognition and tracking within the IVSEE system (FLG), pp. 1–4.
ICPRICPR-2008-LuWC
Gaze tracking by Binocular Vision and LBP features (HL, CW, YWC), pp. 1–4.
ICPRICPR-2008-MakiHM #image #using
Tracking features on a moving object using local image bases (AM, YH, TM), pp. 1–5.
ICPRICPR-2008-MaWHJG #effectiveness
Effective scene matching with local feature representatives (SM, WW, QH, SJ, WG), pp. 1–4.
ICPRICPR-2008-MengLMW #detection
Directional entropy feature for human detection (LM, LL, SM, WW), pp. 1–4.
ICPRICPR-2008-MissaouiF
Optimal feature weighting for the discrete HMM (OM, HF), pp. 1–4.
ICPRICPR-2008-MissaouiF08a
Optimal feature weighting for the continuous HMM (OM, HF), pp. 1–4.
ICPRICPR-2008-OnishiTA #3d #estimation #image #using
3D human posture estimation using the HOG features from monocular image (KO, TT, YA), pp. 1–4.
ICPRICPR-2008-ParamanandR #geometry #higher-order #performance
Efficient geometric matching with higher-order features (CP, ANR), pp. 1–4.
ICPRICPR-2008-ParkPBB #invariant #named
pi-SIFT: A photometric and Scale Invariant Feature Transform (JHP, KWP, SHB, MB), pp. 1–4.
ICPRICPR-2008-RabinDG08a #comparison #distance
Circular Earth Mover’s Distance for the comparison of local features (JR, JD, YG), pp. 1–4.
ICPRICPR-2008-ScalzoBNLT #classification #gender
Feature Fusion Hierarchies for gender classification (FS, GB, MN, LAL, AT), pp. 1–4.
ICPRICPR-2008-SharmaCS #classification #kernel
Bag-of-features kernel eigen spaces for classification (GS, SC, JBS), pp. 1–4.
ICPRICPR-2008-ShenCH #image #retrieval #using
Face image retrieval by using Haar features (BCS, CSC, HHH), pp. 1–4.
ICPRICPR-2008-ShivakumaraHT #detection #performance #using #video
Efficient video text detection using edge features (PS, WH, CLT), pp. 1–4.
ICPRICPR-2008-SpringerK #feature model
Feature selection via decision tree surrogate splits (CS, WPK), pp. 1–5.
ICPRICPR-2008-SuZHL
Segmentation-free recognizer based on enhanced four plane feature for realistic Chinese handwriting (THS, TZ, HJH, CLL), pp. 1–4.
ICPRICPR-2008-TaketomiSY #database #estimation #realtime #using
Real-time camera position and posture estimation using a feature landmark database with priorities (TT, TS, NY), pp. 1–4.
ICPRICPR-2008-TeynorB08a #semantics #visual notation
Semantic grouping of visual features (AT, HB), pp. 1–4.
ICPRICPR-2008-TsaiWY #named
CDIKP: A highly-compact local feature descriptor (YTT, QW, SY), pp. 1–4.
ICPRICPR-2008-TsolakisFD #framework #performance #using
A framework for efficient correspondence using feature interrelations (AGT, MF, AD), pp. 1–4.
ICPRICPR-2008-TsuchiyaF #feature model #using
A method of feature selection using contribution ratio based on boosting (MT, HF), pp. 1–4.
ICPRICPR-2008-UedaT #locality #on the #scalability #using
On the scalability of robot localization using high-dimensional features (TU, KT), pp. 1–4.
ICPRICPR-2008-Vega-PonsRV #algorithm #segmentation #set #using
Active contour algorithm for texture segmentation using a texture feature set (SVP, JLGR, OLV), pp. 1–4.
ICPRICPR-2008-WangWFZ #adaptation #on the
On edge structure based adaptive observation model for facial feature tracking (XW, YW, XF, MZ), pp. 1–4.
ICPRICPR-2008-WangWW
Harris feature vector descriptor (HFVD) (XW, FCW, ZW), pp. 1–4.
ICPRICPR-2008-WangY #feature model #image #realtime
Feature selection for real-time image matching systems (QW, SY), pp. 1–4.
ICPRICPR-2008-WuJP #detection #effectiveness #linear
Effective features based on normal linear structures for detecting microcalcifications in mammograms (ZQW, JJ, YP), pp. 1–4.
ICPRICPR-2008-WuWZ
A cryptosystem based on palmprint feature (XW, KW, DZ), pp. 1–4.
ICPRICPR-2008-XiaRH #invariant #ranking #robust #visual notation
Ranking the local invariant features for the robust visual saliencies (SX, PR, ERH), pp. 1–4.
ICPRICPR-2008-XuZW #detection #feature model #semantics
Semantic feature extraction for accurate eye corner detection (CX, YZ, ZW), pp. 1–4.
ICPRICPR-2008-YamashitaFLK #online
Human tracking based on Soft Decision Feature and online real boosting (TY, HF, SL, MK), pp. 1–4.
ICPRICPR-2008-YangB08a #feature model #recognition #sketching
Feature extraction method based on cascade noise elimination for sketch recognition (JY, HB), pp. 1–4.
ICPRICPR-2008-YangWRY #feature model
Feature Extraction base on Local Maximum Margin Criterion (WY, JW, MR, JY), pp. 1–4.
ICPRICPR-2008-ZhangLHT #automation #classification
Boosting local feature descriptors for automatic objects classification in traffic scene surveillance (ZZ, ML, KH, TT), pp. 1–4.
KDDKDD-2008-BoutsidisMD #analysis #component #feature model
Unsupervised feature selection for principal components analysis (CB, MWM, PD), pp. 61–69.
KDDKDD-2008-ChenW #classification #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-MadaniH #learning #on the
On updates that constrain the features’ connections during learning (OM, JH), pp. 515–523.
KDDKDD-2008-YuDL #feature model
Stable feature selection via dense feature groups (LY, CHQD, SL), pp. 803–811.
SEKESEKE-2008-FernandesWM #feature model #modelling #product line
Feature Modeling for Context-Aware Software Product Lines (PF, CW, LGPM), pp. 758–763.
SEKESEKE-2008-SilvaAAMC #approach
Tailoring an Aspectual Goal-oriented Approach to Model Features (CTLLS, FMRA, JA, AMDM, JBdC), pp. 472–477.
SIGIRSIGIR-2008-DruckMM #learning #using
Learning from labeled features using generalized expectation criteria (GD, GSM, AM), pp. 595–602.
SIGIRSIGIR-2008-NaKKL #information retrieval #proximity
Exploiting proximity feature in bigram language model for information retrieval (SHN, JK, ISK, JHL), pp. 821–822.
SIGIRSIGIR-2008-PengMO #automation #documentation #feature model #retrieval #web
Automatic document prior feature selection for web retrieval (JP, CM, IO), pp. 761–762.
GPCEGPCE-2008-ApelKL #calculus #feature model #java #programming #refinement
Feature featherweight java: a calculus for feature-oriented programming and stepwise refinement (SA, CK, CL), pp. 101–112.
GPCEGPCE-2008-KimKB #composition #feature model #interactive #on the
On the modularity of feature interactions (CHPK, CK, DSB), pp. 23–34.
GPCEGPCE-2008-MendoncaWCC #compilation #feature model #modelling #performance #scalability
Efficient compilation techniques for large scale feature models (MM, AW, KC, DDC), pp. 13–22.
REFSQREFSQ-2008-WebersTS #approach #feature model #modelling #requirements
Connecting Feature Models and AUTOSAR: An Approach Supporting Requirements Engineering in Automotive Industries (WW, CT, KS), pp. 95–108.
SACSAC-2008-BragaOM #estimation #feature model #optimisation #parametricity
A GA-based feature selection and parameters optimization for support vector regression applied to software effort estimation (PLB, ALIO, SRLM), pp. 1788–1792.
SACSAC-2008-BugattiTT #integration #query #similarity
Assessing the best integration between distance-function and image-feature to answer similarity queries (PHB, AJMT, CTJ), pp. 1225–1230.
SACSAC-2008-ChengHVL #image #reduction
Semi-supervised dimensionality reduction in image feature space (HC, KAH, KV, DL), pp. 1207–1211.
SACSAC-2008-FariaM #recognition #scalability #speech
When a mismatch can be good: large vocabulary speech recognition trained with idealized tandem features (AF, NM), pp. 1574–1577.
SACSAC-2008-LiG #detection #network #optimisation #using
TCM-KNN scheme for network anomaly detection using feature-based optimizations (YL, LG), pp. 2103–2109.
SACSAC-2008-MengleG #algorithm #ambiguity #classification #feature model #using
Using ambiguity measure feature selection algorithm for support vector machine classifier (SSRM, NG), pp. 916–920.
SACSAC-2008-RibeiroTT #algorithm #feature model
A new algorithm for data discretization and feature selection (MXR, AJMT, CTJ), pp. 953–954.
SACSAC-2008-SchreckFK #automation #multi #optimisation #towards
Towards automatic feature vector optimization for multimedia applications (TS, DWF, DAK), pp. 1197–1201.
SACSAC-2008-ShaoYN #classification
Strangeness-based feature weighting and classification of gene expression profiles (HS, BY, JHN), pp. 1292–1296.
SACSAC-2008-TakanoC #documentation #feature model #feedback
A light-weight feedback method for reconstructing a document vector space on a feature extraction model (KT, XC), pp. 1169–1170.
SACSAC-2008-TanWC #categorisation #performance #ranking
An efficient feature ranking measure for text categorization (ST, YW, XC), pp. 407–413.
SACSAC-2008-YuLLM #configuration management
Configuring features with stakeholder goals (YY, JCSdPL, AL, JM), pp. 645–649.
SACSAC-2008-ZhangMD #feature model #fuzzy #image #retrieval #set #using
Texture feature extraction and description using fuzzy set of main dominant directions of variable scales in content-based medical image retrieval (GZ, ZMM, LD), pp. 1760–1761.
ATEMATEM-J-2006-HeymansSTBMC #diagrams #feature model
Evaluating formal properties of feature diagram languages (PH, PYS, JCT, YB, RM, AC), pp. 281–302.
SPLCSPLC-2008-ChoLK #approach #aspect-oriented #dependence
Feature Relation and Dependency Management: An Aspect-Oriented Approach (HC, KL, KCK), pp. 3–11.
SPLCSPLC-2008-CzarneckiSW #feature model #modelling
Sample Spaces and Feature Models: There and Back Again (KC, SS, AW), pp. 22–31.
SPLCSPLC-2008-HartmannT #diagrams #feature model #multi #product line #using #variability
Using Feature Diagrams with Context Variability to Model Multiple Product Lines for Software Supply Chains (HH, TT), pp. 12–21.
SPLCSPLC-2008-WhiteSBTC #automation #fault #feature model #modelling #product line
Automated Diagnosis of Product-Line Configuration Errors in Feature Models (JW, DCS, DB, PT, ARC), pp. 225–234.
CAVCAV-2008-DSouzaG
Conflict-Tolerant Features (DD, MG), pp. 227–239.
ICLPICLP-2008-CodishLS #constraints #partial order #problem
Telecommunications Feature Subscription as a Partial Order Constraint Problem (MC, VL, PJS), pp. 749–753.
ECSAECSA-2007-LoulouKJD #architecture #design
Formal Design of Structural and Dynamic Features of Publish/Subscribe Architectural Styles (IL, AHK, MJ, KD), pp. 44–59.
ASEASE-2007-Gawley #automation #feature model #identification #modelling #variability
Automating the identification of variability realisation techniques from feature models (RG), pp. 555–558.
ASEASE-2007-LiuMPR #execution #feature model #information retrieval
Feature location via information retrieval based filtering of a single scenario execution trace (DL, AM, DP, VR), pp. 234–243.
ASEASE-2007-ShiriHR #analysis #feature model #interactive #maintenance #perspective
Feature interaction analysis: a maintenance perspective (MS, JH, JR), pp. 437–440.
CASECASE-2007-00010DAR #behaviour #feature model #realtime
A Micropositioning System with Real-Time Feature Extraction Capability for Quantifying C. elegans Locomotive Behavior (WW, YS, SJD, MA, PJR), pp. 243–248.
CASECASE-2007-GarciaV #automation #configuration management #feature model #visual notation
Automated Feature Selection Methodology for Reconfigurable Automated Visual Inspection Systems (HCG, JRV), pp. 542–547.
CASECASE-2007-YangM #approach #automation #feature model #interactive #matrix #verification
Automatic Feasibility Verification of Object Configurations: A New Approach Based on Feature Interaction Matrices (FY, MMM), pp. 686–691.
CASECASE-2007-ZhangBGL #feature model #hybrid #monitoring
A Hybrid Model with a Weighted Voting Scheme for Feature Selection in Machinery Condition Monitoring (KZ, ADB, FG, YL), pp. 424–429.
DACDAC-2007-KumarMCTH #approach #estimation #multi #performance #probability
A Probabilistic Approach to Model Resource Contention for Performance Estimation of Multi-featured Media Devices (AK, BM, HC, BDT, YH), pp. 726–731.
DATEDATE-2007-KokkelerSKK #detection
Cyclostationary feature detection on a tiled-SoC (ABJK, GJMS, TK, JK), pp. 171–176.
DRRDRR-2007-JoutelEBE #classification #feature model
Curvelets based feature extraction of handwritten shapes for ancient manuscripts classification (GJ, VE, SB, HE).
HTHT-2007-LeveringCY #classification #html #visual notation
Visual features in genre classification of html (RL, MC, LY), pp. 51–52.
HTHT-2007-SteinH #case study #matter #wiki
Does it matter who contributes: a study on featured articles in the german wikipedia (KS, CH), pp. 171–174.
ICDARICDAR-2007-AbedM #comparison #feature model #preprocessor #recognition
Comparison of Different Preprocessing and Feature Extraction Methods for Offline Recognition of Handwritten ArabicWords (HEA, VM), pp. 974–978.
ICDARICDAR-2007-AmorA #approach #multi
An Approach for Multifont Arabic Characters Features Extraction Based on Contourlet Transform (NBA, NEBA), pp. 1048–1052.
ICDARICDAR-2007-BhardwajSSS #on the #verification
On the Use of Lexeme Features for Writer Verification (AB, AS, HS, SNS), pp. 1088–1092.
ICDARICDAR-2007-BhattacharyaGP #online #recognition
Direction Code Based Features for Recognition of Online Handwritten Characters of Bangla (UB, BKG, SKP), pp. 58–62.
ICDARICDAR-2007-ChouGC #classification #multi #recognition #using
Recognition of Fragmented Characters Using Multiple Feature-Subset Classifiers (CHC, CYG, FC), pp. 198–202.
ICDARICDAR-2007-HuangSHFN #approach #difference #recognition #using
An SVM-Based High-accurate Recognition Approach for Handwritten Numerals by Using Difference Features (KH, JS, YH, KF, SN), pp. 589–593.
ICDARICDAR-2007-ImdadBERE #identification #using
Writer Identification Using Steered Hermite Features and SVM (AI, SB, VE, CRM, HE), pp. 839–843.
ICDARICDAR-2007-MengZSZ #documentation #image #multi #retrieval
Document Images Retrieval Based on Multiple Features Combination (GM, NZ, YS, YZ), pp. 143–147.
ICDARICDAR-2007-MS #encoding #online #recognition
A Feature based on Encoding the Relative Position of a Point in the Character for Online Handwritten Character Recognition (DM, MKS), pp. 1014–1017.
ICDARICDAR-2007-NguyenBML #classification #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-PrasanthBSRM #online #using
Elastic Matching of Online Handwritten Tamil and Telugu Scripts Using Local Features (LP, VB, RS, GVR, DM), pp. 1028–1032.
ICDARICDAR-2007-RanzatoL #documentation #image #invariant
A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images (MR, YL), pp. 1213–1217.
ICDARICDAR-2007-SchlapbachB #identification #online
Fusing Asynchronous Feature Streams for On-line Writer Identification (AS, HB), pp. 103–107.
ICDARICDAR-2007-ShimanukiKW #design
Extracting Features of Paper-made Objects Recognized from Origami Books Based on Design Knowledge (HS, JK, TW), pp. 1203–1207.
ICDARICDAR-2007-TanakaG #using
Autonomous Text Capturing Robot Using Improved DCT Feature and Text Tracking (MT, HG), pp. 1178–1182.
ICDARICDAR-2007-VamvakasGPS #feature model #performance #recognition #reduction
An Efficient Feature Extraction and Dimensionality Reduction Scheme for Isolated Greek Handwritten Character Recognition (GV, BG, SP, NS), pp. 1073–1077.
ICDARICDAR-2007-XiCLWSJ07a #clustering #segmentation
Character Line Segmentation Based on Feature Clustering (YX, YC, QL, LW, FS, DJ), pp. 402–406.
ICDARICDAR-2007-ZiaratbanFF #feature model #recognition #using
Language-Based Feature Extraction Using Template-Matching In Farsi/Arabic Handwritten Numeral Recognition (MZ, KF, FF), pp. 297–301.
CSMRCSMR-2007-GreevyGD #developer #how
How Developers Develop Features (OG, TG, SD), pp. 265–274.
CSMRCSMR-2007-KanstrenHK #case study #experience #legacy #testing
Integrating and Testing a System-Wide Feature in a Legacy System: An Experience Report (TK, MH, KK), pp. 203–212.
CSMRCSMR-2007-PengWZ #adaptation #component #evolution #feature model
A Feature-Oriented Adaptive Component Model for Dynamic Evolution (XP, YW, WZ), pp. 49–57.
ICPCICPC-2007-KothariDSM #comprehension #convergence #evolution #implementation
Reducing Program Comprehension Effort in Evolving Software by Recognizing Feature Implementation Convergence (JK, TD, AS, SM), pp. 17–26.
ICPCICPC-2007-LienhardGN #dependence #detection
Tracking Objects to Detect Feature Dependencies (AL, OG, ON), pp. 59–68.
ICSMEICSM-2007-FokaefsTC #identification #named #smell
JDeodorant: Identification and Removal of Feature Envy Bad Smells (MF, NT, AC), pp. 519–520.
ICSMEICSM-2007-WalkinshawRW #feature model #using
Feature Location and Extraction using Landmarks and Barriers (NW, MR, MW), pp. 54–63.
WCREWCRE-2007-FarahL #comprehension #modelling
Temporal Exploration of Software Models: A Tool Feature to Enhance Software Understanding (HF, TCL), pp. 41–49.
SEFMSEFM-2007-ReevesS #refinement
Feature Refinement (SR, DS), pp. 371–380.
HCIDHM-2007-LuoYZ #identification
A Method for Gene Identification by Dynamic Feature Choosing (JL, LY, XZ), pp. 678–683.
HCIDHM-2007-XiangZ #retrieval
Motion Retrieval Based on Temporal-Spatial Features by Decision Tree (JX, HZ), pp. 224–233.
HCIHCI-AS-2007-JiangSZF #design #feature model #interactive
An Interactive Evolutionary Design System with Feature Extraction (XJ, SS, TZ, SF), pp. 1085–1094.
HCIHCI-MIE-2007-HuLYS #modelling
Modeling of Places Based on Feature Distribution (YH, CWL, JYY, BJS), pp. 1019–1027.
HCIHCI-MIE-2007-JuSK #game studies #people #quote #using
“Shooting a Bird”: Game System Using Facial Feature for the Handicapped People (JJ, YS, EYK), pp. 642–648.
HCIHCI-MIE-2007-TakashimaT #behaviour #low level #video
Sharing Video Browsing Style by Associating Browsing Behavior with Low-Level Features of Videos (AT, YT), pp. 518–526.
HCIHIMI-IIE-2007-TaguchiAT #analysis
Information on the Causal Relationship Between Store kaizen and Store Features That Attract Customers by Covariance Structural Analysis (YT, YA, TT), pp. 973–982.
VISSOFTVISSOFT-2007-CosmaM #distributed #visualisation
Distributable Features View: Visualizing the Structural Characteristics of Distributed Software Systems (DCC, RM), pp. 55–62.
VISSOFTVISSOFT-2007-RothlisbergerGL
Feature-centric Environment (DR, OG, AL), pp. 150–151.
AdaEuropeAdaEurope-2007-PanunzioV #analysis #metamodelling #modelling #process
A Metamodel-Driven Process Featuring Advanced Model-Based Timing Analysis (MP, TV), pp. 128–141.
CAiSECAiSE-2007-WeberRR #information management
Change Patterns and Change Support Features in Process-Aware Information Systems (BW, SR, MR), pp. 574–588.
ICEISICEIS-AIDSS-2007-CuellarDP #algorithm #hybrid #network #problem
Problems and Features of Evolutionary Algorithms to Build Hybrid Training Methods for Recurrent Neural Networks (MPC, MD, MdCPJ), pp. 204–211.
CIKMCIKM-2007-HouleG #feature model
A correlation-based model for unsupervised feature selection (MEH, NG), pp. 897–900.
CIKMCIKM-2007-Metzler #automation #feature model #information retrieval #markov #random
Automatic feature selection in the markov random field model for information retrieval (DM), pp. 253–262.
ECIRECIR-2007-MasegosaJJ #independence #predict
Evaluating Query-Independent Object Features for Relevancy Prediction (ARM, HJ, JMJ), pp. 283–294.
ECIRECIR-2007-NeumayerR #classification #information retrieval #integration #music
Integration of Text and Audio Features for Genre Classification in Music Information Retrieval (RN, AR), pp. 724–727.
ECIRECIR-2007-PanLZTC #retrieval #video
Retrieval Method for Video Content in Different Format Based on Spatiotemporal Features (XP, JL, YZ, ST, JC), pp. 728–731.
ECIRECIR-2007-SzlavikTL #documentation #generative #xml
Feature- and Query-Based Table of Contents Generation for XML Documents (ZS, AT, ML), pp. 456–467.
ICMLICML-2007-AndoZ #generative #learning
Two-view feature generation model for semi-supervised learning (RKA, TZ), pp. 25–32.
ICMLICML-2007-CaoSSYC #feature model #kernel
Feature selection in a kernel space (BC, DS, JTS, QY, ZC), pp. 121–128.
ICMLICML-2007-ChenJ #classification #feature model #set
Minimum reference set based feature selection for small sample classifications (XwC, JCJ), pp. 153–160.
ICMLICML-2007-DavisCRP #approach #predict #process
An integrated approach to feature invention and model construction for drug activity prediction (JD, VSC, SR, DP), pp. 217–224.
ICMLICML-2007-LeeCVK #learning #multi
Learning a meta-level prior for feature relevance from multiple related tasks (SIL, VC, DV, DK), pp. 489–496.
ICMLICML-2007-ParrPLL #approximate #generative
Analyzing feature generation for value-function approximation (RP, CPW, LL, MLL), pp. 737–744.
ICMLICML-2007-SongSGBB #dependence #estimation #feature model
Supervised feature selection via dependence estimation (LS, AJS, AG, KMB, JB), pp. 823–830.
ICMLICML-2007-ZhaoL #feature model #learning
Spectral feature selection for supervised and unsupervised learning (ZZ, HL), pp. 1151–1157.
KDDKDD-2007-ArchakGI #exclamation #mining #power of
Show me the money!: deriving the pricing power of product features by mining consumer reviews (NA, AG, PGI), pp. 56–65.
KDDKDD-2007-ChaovalitwongseFS #classification #process
Support feature machine for classification of abnormal brain activity (WAC, YJF, RCS), pp. 113–122.
KDDKDD-2007-DasguptaDHJM #classification #feature model
Feature selection methods for text classification (AD, PD, BH, VJ, MWM), pp. 230–239.
KDDKDD-2007-TangWXZ #clustering #perspective
Enhancing semi-supervised clustering: a feature projection perspective (WT, HX, SZ, JW), pp. 707–716.
MLDMMLDM-2007-CaoH #feature model
Affine Feature Extraction: A Generalization of the Fukunaga-Koontz Transformation (WC, RMH), pp. 160–173.
MLDMMLDM-2007-ChengCJY #feature model
Nonlinear Feature Selection by Relevance Feature Vector Machine (HC, HC, GJ, KY), pp. 144–159.
MLDMMLDM-2007-SilvaGF #identification
One Lead ECG Based Personal Identification with Feature Subspace Ensembles (HS, HG, ALNF), pp. 770–783.
MLDMMLDM-2007-ZagorisPK #algorithm #fuzzy #reduction #self #using
Color Reduction Using the Combination of the Kohonen Self-Organized Feature Map and the Gustafson-Kessel Fuzzy Algorithm (KZ, NP, IK), pp. 703–715.
SIGIRSIGIR-2007-ClarkeADW #web
The influence of caption features on clickthrough patterns in web search (CLAC, EA, STD, RWW), pp. 135–142.
SIGIRSIGIR-2007-CormackHS #mobile #re-engineering
Feature engineering for mobile (SMS) spam filtering (GVC, JMGH, EPS), pp. 871–872.
SIGIRSIGIR-2007-FranzX #multi #segmentation #using
Story segmentation of broadcast news in Arabic, Chinese and English using multi-window features (MF, JMX), pp. 703–704.
SIGIRSIGIR-2007-GengLQL #feature model #ranking
Feature selection for ranking (XG, TYL, TQ, HL), pp. 407–414.
SIGIRSIGIR-2007-HeCL #detection
Analyzing feature trajectories for event detection (QH, KC, EPL), pp. 207–214.
SIGIRSIGIR-2007-RaghavanA #algorithm #feedback #interactive
An interactive algorithm for asking and incorporating feature feedback into support vector machines (HR, JA), pp. 79–86.
MODELSMoDELS-2007-JayaramanWEG #analysis #composition #detection #feature model #interactive #product line #using
Model Composition in Product Lines and Feature Interaction Detection Using Critical Pair Analysis (PKJ, JW, AME, HG), pp. 151–165.
MODELSMoDELS-2007-JayaramanWEG #analysis #composition #detection #feature model #interactive #product line #using
Model Composition in Product Lines and Feature Interaction Detection Using Critical Pair Analysis (PKJ, JW, AME, HG), pp. 151–165.
TOOLSTOOLS-EUROPE-2007-HundtMPS #feature model #product line
Improving Alignment of Crosscutting Features with Code in Product Line Engineering (CH, KM, CP, DS), pp. 417–436.
RERE-2007-DorrHKLA #user satisfaction
Built-in User Satisfaction — Feature Appraisal and Prioritization with AMUSE (JD, SH, DK, DL, PA), pp. 101–110.
REFSQREFSQ-2007-Poppleton #development #feature model #specification #towards
Towards Feature-Oriented Specification and Development with Event-B (MP), pp. 367–381.
SACSAC-2007-QiT #array #feature model #ontology
Integrating gene ontology into discriminative powers of genes for feature selection in microarray data (JQ, JT), pp. 430–434.
SACSAC-2007-TsengSWL #image #visual notation #web
Web image annotation by fusing visual features and textual information (VST, JHS, BWW, YML), pp. 1056–1060.
SACSAC-2007-UbayashiN #feature model #modelling
Context-aware feature-oriented modeling with an aspect extension of VDM (NU, SN), pp. 1269–1274.
GTTSEGTTSE-2007-SeguraBCT #automation #feature model #graph transformation #modelling #using
Automated Merging of Feature Models Using Graph Transformations (SS, DB, ARC, PT), pp. 489–505.
ICSEICSE-2007-KojarskiL #aspect-oriented #feature model #framework #identification #interactive #multi
Identifying Feature Interactions in Multi-Language Aspect-Oriented Frameworks (SK, DHL), pp. 147–157.
ICSEICSE-2007-TrujilloBD #case study #development #modelling
Feature Oriented Model Driven Development: A Case Study for Portlets (ST, DSB, OD), pp. 44–53.
SPLCSPLC-2007-BragancaM #automation #case study #diagrams #feature model #modelling #product line
Automating Mappings between Use Case Diagrams and Feature Models for Software Product Lines (AB, RJM), pp. 3–12.
SPLCSPLC-2007-CzarneckiW #diagrams #feature model #logic
Feature Diagrams and Logics: There and Back Again (KC, AW), pp. 23–34.
SPLCSPLC-2007-JanotaK #feature model #higher-order #logic #modelling #reasoning
Reasoning about Feature Models in Higher-Order Logic (MJ, JRK), pp. 13–22.
SPLCSPLC-2007-KastnerAB #aspectj #case study #implementation #using
A Case Study Implementing Features Using AspectJ (CK, SA, DSB), pp. 223–232.
ASEASE-2006-Dhungana #architecture #modelling #product line #variability
Integrated Variability Modeling of Features and Architecture in Software Product Line Engineering (DD), pp. 327–330.
CASECASE-2006-YoungSB #implementation #interactive
Implementing Bubblegrams: The Use of Haar-Like Features for Human-Robot Interaction (JEY, ES, JEB), pp. 298–303.
DocEngDocEng-2006-Ruiz-RicoGR #automation #feature model #named #ranking
NEWPAR: an automatic feature selection and weighting schema for category ranking (FRR, JLVG, MCRS), pp. 128–137.
DRRDRR-2006-KhanAC #automation
Address block features for image-based automated mail orientation (MSK, HBA, WTC).
DRRDRR-2006-Sun #fuzzy
HCCR by contour-based elastic mesh fuzzy feature (LS).
DRRDRR-2006-WangZXWG #feature model #image #recognition #robust
Robust feature extraction for character recognition based on binary images (LW, LZ, YX, ZW, HG).
SIGMODSIGMOD-2006-ShenSN #database #multi #music #named
InMAF: indexing music databases via multiple acoustic features (JS, JS, AHHN), pp. 778–780.
VLDBVLDB-2006-0002OIA #documentation #named #xml
FIX: Feature-based Indexing Technique for XML Documents (NZ, MTÖ, IFI, AA), pp. 259–270.
ICPCICPC-2006-PoshyvanykMRGA #identification #probability #ranking #semantics
Combining Probabilistic Ranking and Latent Semantic Indexing for Feature Identification (DP, AM, VR, YGG, GA), pp. 137–148.
ICSMEICSM-2006-JiangGSEW #comprehension #industrial
Software Feature Understanding in an Industrial Setting (MJ, MG, SS, DE, NW), pp. 66–67.
ICSMEICSM-2006-NgoT #fault #maintenance
A Method to Aid Recovery and Maintenance of the Input Error Correction Features (MNN, HBKT), pp. 360–369.
WCREWCRE-2006-KothariDMS #canonical #on the
On Computing the Canonical Features of Software Systems (JK, TD, SM, AS), pp. 93–102.
FMFM-2006-AiguierBG #interactive #specification #static analysis
Feature Specification and Static Analysis for Interaction Resolution (MA, KB, PLG), pp. 364–379.
FMFM-2006-HofnerKM #algebra
Feature Algebra (PH, RK, BM), pp. 300–315.
CHICHI-2006-KramerOF #communication #using
Using linguistic features to measure presence in computer-mediated communication (ADIK, LMO, SRF), pp. 913–916.
SOFTVISSOFTVIS-2006-BohnetD #feature model #graph #visual notation
Visual exploration of function call graphs for feature location in complex software systems (JB, JD), pp. 95–104.
ICEISICEIS-ISAS-2006-RoubtsovaR #requirements #reuse
A Feature Computation Tree Model to Specify Requirements and Reuse (EER, SAR), pp. 118–125.
CIKMCIKM-2006-AssfalgBK #3d #classification #kernel #named #string
3DString: a feature string kernel for 3D object classification on voxelized data (JA, KMB, HPK), pp. 198–207.
CIKMCIKM-2006-LuPLA #feature model #identification #machine learning #query
Coupling feature selection and machine learning methods for navigational query identification (YL, FP, XL, NA), pp. 682–689.
CIKMCIKM-2006-OlssonO #classification
Combining feature selectors for text classification (JSO, DWO), pp. 798–799.
ECIRECIR-2006-WilkinsFGS #automation #multi
Automatic Determination of Feature Weights for Multi-feature CBIR (PW, PF, CG, AFS), pp. 527–530.
ECIRECIR-2006-ZhangDC #detection
Combining Short and Long Term Audio Features for TV Sports Highlight Detection (BZ, WD, LC), pp. 472–475.
ICMLICML-2006-GlobersonR #learning #robust
Nightmare at test time: robust learning by feature deletion (AG, STR), pp. 353–360.
ICMLICML-2006-GorurJR #infinity
A choice model with infinitely many latent features (DG, FJ, CER), pp. 361–368.
ICMLICML-2006-RossOZ
Combining discriminative features to infer complex trajectories (DAR, SO, RSZ), pp. 761–768.
ICMLICML-2006-ShengL #algorithm #testing
Feature value acquisition in testing: a sequential batch test algorithm (VSS, CXL), pp. 809–816.
ICMLICML-2006-SinghiL #bias #classification #learning #set
Feature subset selection bias for classification learning (SKS, HL), pp. 849–856.
ICMLICML-2006-SongE #human-computer #interface #learning
Classifying EEG for brain-computer interfaces: learning optimal filters for dynamical system features (LS, JE), pp. 857–864.
ICMLICML-2006-SunL
Iterative RELIEF for feature weighting (YS, JL), pp. 913–920.
ICMLICML-2006-VeeramachaneniOA #detection
Active sampling for detecting irrelevant features (SV, EO, PA), pp. 961–968.
ICPRICPR-v1-2006-ArzhaevaGT #classification #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-BabaMA #geometry #using
A Unified Camera Calibration Using Geometry and Blur of Feature Points (MB, MM, NA), pp. 816–819.
ICPRICPR-v1-2006-BauckhageK #detection #multi #performance
Fast, Illumination Insensitive Face Detection Based on Multilinear Techniques and Curvature Features (CB, TK), pp. 507–510.
ICPRICPR-v1-2006-ChengZS #detection
Boosted Gabor Features Applied to Vehicle Detection (HC, NZ, CS), pp. 662–666.
ICPRICPR-v1-2006-ChowdhuryGWM #detection #feature model
Note on Feature Selection for Polyp Detection in CT Colonography (TAC, OG, PFW, AAM), pp. 1017–1021.
ICPRICPR-v1-2006-FuCLR #classification #feature model #image
Boosted Band Ratio Feature Selection for Hyperspectral Image Classification (ZF, TC, NL, ARK), pp. 1059–1062.
ICPRICPR-v1-2006-GaoWFZ #recognition #using
Face Recognition Using Most Discriminative Local and Global Features (YG, YW, XF, XZ), pp. 351–354.
ICPRICPR-v1-2006-HanXG #clustering #segmentation #video
Video Foreground Segmentation Based on Sequential Feature Clustering (MH, WX, YG), pp. 492–496.
ICPRICPR-v1-2006-LangsPDRB #feature model #modelling
Active Feature Models (GL, PP, RD, MR, HB), pp. 417–420.
ICPRICPR-v1-2006-LiHWW #behaviour #image #modelling #recognition
Behavior Modeling and Recognition Based on Space-Time Image Features (HL, ZH, YW, FW), pp. 243–246.
ICPRICPR-v1-2006-LoY #detection #multi
Shadow Detection by Integrating Multiple Features (KHL, MTY), pp. 743–746.
ICPRICPR-v1-2006-MicheloniF
Focusing on Target’s Features while Tracking (CM, GLF), pp. 836–839.
ICPRICPR-v1-2006-MoritaniHS #feature model #realtime
Real-Time Object Tracking without Feature Extraction (TM, SH, KS), pp. 747–750.
ICPRICPR-v1-2006-NieseAM #estimation #feature model
A Stereo and Color-based Method for Face Pose Estimation and Facial Feature Extraction (RN, AAH, BM), pp. 299–302.
ICPRICPR-v1-2006-SunSM #classification #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-TongJ #multi #probability
Multiview Facial Feature Tracking with a Multi-modal Probabilistic Model (YT, QJ), pp. 307–310.
ICPRICPR-v1-2006-TongWZJ #multi #using
Facial Feature Tracking using a Multi-State Hierarchical Shape Model under Varying Face Pose and Facial Expression (YT, YW, ZZ, QJ), pp. 283–286.
ICPRICPR-v1-2006-WeiB #data analysis #segmentation #statistics #using
Unsupervised Segmentation Using Gabor Wavelets and Statistical Features in LIDAR Data Analysis (HW, MB), pp. 667–670.
ICPRICPR-v1-2006-WuNC #feature model #locality
Biologically Inspired Hierarchical Model for Feature Extraction and Localization (LW, PN, LNC), pp. 259–262.
ICPRICPR-v1-2006-XuS #robust
A Robust and Accurate Method for Pupil Features Extra (ZX, PS), pp. 437–440.
ICPRICPR-v1-2006-YangZJY #analysis #feature model
Unsupervised Discriminant Projection Analysis for Feature Extraction (JY, DZ, ZJ, JYY), pp. 904–907.
ICPRICPR-v1-2006-ZhuJ #detection #invariant #realtime #robust
Robust Pose Invariant Facial Feature Detection and Tracking in Real-Time (ZZ, QJ), pp. 1092–1095.
ICPRICPR-v2-2006-ArivazhaganGK #classification #statistics #using
Texture classification using Curvelet Statistical and Co-occurrence Features (SA, LG, TGSK), pp. 938–941.
ICPRICPR-v2-2006-BertolamiB #classification #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-ChenCC #comparison
A Comparison of Texture Features Based on SVM and SOM (CMC, CCC, CCC), pp. 630–633.
ICPRICPR-v2-2006-ChenW #analysis #component #independence #segmentation #using
Texture Segmentation Using Independent Component Analysis of Gabor Features (YC, RW), pp. 147–150.
ICPRICPR-v2-2006-ChenY #modelling #using #video
Exploiting High Dimensional Video Features Using Layered Gaussian Mixture Models (DC, JY), pp. 1078–1081.
ICPRICPR-v2-2006-ChoiLY #classification #feature model #using
Feature Extraction for Bank Note Classification Using Wavelet Transform (EC, JL, JY), pp. 934–937.
ICPRICPR-v2-2006-FloreaBRB #image #representation #using
Using texture-based symbolic features for medical image representation (FF, EB, AR, AB), pp. 946–949.
ICPRICPR-v2-2006-FrintropJC
Pay Attention When Selecting Features (SF, PJ, HIC), pp. 163–166.
ICPRICPR-v2-2006-FuLHB #image #retrieval #using
Content-based Image Retrieval Using Gabor-Zernike Features (XF, YL, RWH, SB), pp. 417–420.
ICPRICPR-v2-2006-GanD #relational #using
Differentiating Between Many Similar Features using Relational Information in Space and Scale (TSYG, TD), pp. 638–641.
ICPRICPR-v2-2006-GuptaD #detection #multi #using
Texture Edge Detection using Multi-resolution Features and SOM (LG, SD), pp. 199–202.
ICPRICPR-v2-2006-HuangCX #feature model
A Wrapper for Feature Selection Based on Mutual Information (JH, YC, XX), pp. 618–621.
ICPRICPR-v2-2006-InoueNK #analysis #feature model #kernel #recognition #string #using
Historical Hand-Written String Recognition by Non-linear Discriminant Analysis using Kernel Feature Selection (RI, HN, NK), pp. 1094–1097.
ICPRICPR-v2-2006-KanaujiaM
Recognizing Facial Expressions by Tracking Feature Shapes (AK, DNM), pp. 33–38.
ICPRICPR-v2-2006-KhanKKA #dependence #online #verification
On-Line Signature Verification by Exploiting Inter-Feature Dependencies (MKK, MAK, MAUK, IA), pp. 796–799.
ICPRICPR-v2-2006-KimYK #robust
Background Robust Object Labeling by Voting of Weight-Aggregated Local Features (SK, KJY, ISK), pp. 219–222.
ICPRICPR-v2-2006-KrizekKH #feature model #set
Feature selection based on the training set manipulation (PK, JK, VH), pp. 658–661.
ICPRICPR-v2-2006-LettnerS #recognition
Texture and Profile Features for Drawing Media Recognition in Underdrawings (ML, RS), pp. 308–311.
ICPRICPR-v2-2006-LiangZ #feature model #linear
Feature selection for linear support vector machines (ZL, TZ), pp. 606–609.
ICPRICPR-v2-2006-LiLG #multi
Multi-Resolution Curve Alignment Based on Salient Features (ZL, XL, CG), pp. 357–360.
ICPRICPR-v2-2006-LiLL #framework #geometry #multi #using
A Geometric Active Contour Framework using Multi-Cue and Local Feature (ZL, QL, HL), pp. 113–116.
ICPRICPR-v2-2006-LiLW #feature model #hybrid #ranking
A Hybrid Method of Unsupervised Feature Selection Based on Ranking (YL, BLL, ZFW), pp. 687–690.
ICPRICPR-v2-2006-Liu #classification #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-LiuSXR #complexity #feature model #image
Image Complexity and Feature Extraction for Steganalysis of LSB Matching Steganography (QL, AHS, JX, BR), pp. 267–270.
ICPRICPR-v2-2006-MahiniKDD #locality #performance
An Efficient Features — Based License Plate Localization Method (HM, SK, FD, FD), pp. 841–844.
ICPRICPR-v2-2006-MunguiaGS #image
Matching Images Features in a Wide Base Line with ICA Descriptors (RM, AG, AS), pp. 159–162.
ICPRICPR-v2-2006-RaoGSK #image
A Heterogeneous Feature-based Image Alignment Method (CR, YG, HSS, RK), pp. 345–350.
ICPRICPR-v2-2006-RinnhoferBJS #alloy #feature model
Feature Extraction from Micrographs of Forged Nickel Based Alloy (AR, WB, GJ, MS), pp. 391–394.
ICPRICPR-v2-2006-SaraM #invariant #named #recognition #towards
FAIR: Towards A New Feature for Affinely-Invariant Recognition (RS, MM), pp. 412–416.
ICPRICPR-v2-2006-Sarkar #classification #image #visual notation
Image classification: Classifying distributions of visual features (PS), pp. 472–475.
ICPRICPR-v2-2006-ShiratoriGK #performance #using
An Efficient Text Capture Method for Moving Robots Using DCT Feature and Text Tracking (HS, HG, HK), pp. 1050–1053.
ICPRICPR-v2-2006-SomolP #algorithm #feature model #keyword #multi #prototype #using
Multi-Subset Selection for Keyword Extraction and Other Prototype Search Tasks Using Feature Selection Algorithms (PS, PP), pp. 736–739.
ICPRICPR-v2-2006-SunV #detection #linear #multi #performance #using
Fast Linear Feature Detection Using Multiple Directional Non-Maximum Suppression (CS, PV), pp. 288–291.
ICPRICPR-v2-2006-TongWMI #3d #optimisation #representation
Evolutionary Optimization of Feature Representation for 3D Point-based (XT, HSW, BM, HHSI), pp. 707–710.
ICPRICPR-v2-2006-TsuchiyaF #classification #visual notation
Evaluating Feature Importance for Object Classification in Visual Surveillance (MT, HF), pp. 978–981.
ICPRICPR-v2-2006-YangL #analysis #automation #component
Automatic Physiognomic Analysis by Classifying Facial Component Feature (HDY, SWL), pp. 1212–1215.
ICPRICPR-v2-2006-YaslanC #classification #feature model #music #using
Audio Music Genre Classification Using Different Classifiers and Feature Selection Methods (YY, ), pp. 573–576.
ICPRICPR-v2-2006-YuW06a #algorithm
Genetic-based K-means algorithm for selection of feature variables (ZY, HSW), pp. 744–747.
ICPRICPR-v2-2006-ZhangJHW #detection #using
Learning-Based License Plate Detection Using Global and Local Features (HZ, WJ, XH, QW), pp. 1102–1105.
ICPRICPR-v3-2006-AlahariPJ #learning #online #recognition
Learning Mixtures of Offline and Online features for Handwritten Stroke Recognition (KA, SLP, CVJ), pp. 379–382.
ICPRICPR-v3-2006-BeveridgeSR #classification #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-ChenY06a #adaptation #equation #image
A new adaptive diffusion equation for image noise removal and feature preservation (SC, XY), pp. 885–888.
ICPRICPR-v3-2006-FarajB #authentication
Motion Features from Lip Movement for Person Authentication (MIF, JB), pp. 1059–1062.
ICPRICPR-v3-2006-LeePL #image #kernel #re-engineering
Face Reconstruction with Low Resolution Facial Images by Feature Vector Projection in Kernel Space (SWL, JP, SWL), pp. 1179–1182.
ICPRICPR-v3-2006-LiGYCG #feature model
Facial Feature Selection Based on SVMs by Regularized Risk Minimization (WL, WG, LY, WC, XG), pp. 540–543.
ICPRICPR-v3-2006-LiuW #algorithm #analysis #component #feature model #recognition #search-based
Feature Extraction with Genetic Algorithms Based Nonlinear Principal Component Analysis for Face Recognition (NL, HW), pp. 461–464.
ICPRICPR-v3-2006-LiuW06a #multi #recognition
Facial Expression Recognition Based on Fusion of Multiple Gabor Features (WL, ZW), pp. 536–539.
ICPRICPR-v3-2006-LiuYLM #recognition #robust #similarity
Occlusion Robust Face Recognition with Dynamic Similarity Features (QL, WY, HL, SM), pp. 544–547.
ICPRICPR-v3-2006-PranckevicieneHS #feature model
Class Separability in Spaces Reduced By Feature Selection (EP, TH, RLS), pp. 254–257.
ICPRICPR-v3-2006-QinSL #analysis #feature model #performance
Efficient Feature Extraction Based on Regularized Uncorrelated Chernoff Discriminant Analysis (AKQ, PNS, ML), pp. 125–128.
ICPRICPR-v3-2006-SagheerTTAM #approach #feature model #multi #performance #problem
Fast Feature Extraction Approach for Multi-Dimension Feature Space Problems (AES, NT, RiT, DA, SM), pp. 417–420.
ICPRICPR-v3-2006-XuanZCZSF #distance #feature model
Feature Selection based on the Bhattacharyya Distance (GX, XZ, PC, ZZ, YQS, DF), pp. 1232–1235.
ICPRICPR-v3-2006-XueD #2d #3d #locality #multi #using
3D+2D Face Localization Using Boosting in Multi-Modal Feature Space (FX, XD), pp. 499–502.
ICPRICPR-v3-2006-ZhengYYWY #agile #feature model #recognition
A Complete and Rapid Feature Extraction Method for Face Recognition (YJZ, JYY, JY, XW, DY), pp. 469–472.
ICPRICPR-v4-2006-ArmandBM #verification
Off-line Signature Verification based on the Modified Direction Feature (SA, MB, VM), pp. 509–512.
ICPRICPR-v4-2006-ChaiWJZ #novel #recognition
A Novel Human Gait Recognition Method by Segmenting and Extracting the Region Variance Feature (YC, QW, JJ, RZ), pp. 425–428.
ICPRICPR-v4-2006-ChikkerurPJRB #locality #representation #using
Fingerprint Representation Using Localized Texture Features (SC, SP, AJ, NKR, RMB), pp. 521–524.
ICPRICPR-v4-2006-CristaniCM #3d #adaptation #estimation #integration #segmentation
Adaptive Feature Integration for Segmentation of 3D Data by Unsupervised Density Estimation (MC, UC, VM), pp. 21–24.
ICPRICPR-v4-2006-Gonzalez-JimenezA #authentication
Pose Correction and Subject-Specific Features for Face Authentication (DGJ, JLAC), pp. 602–605.
ICPRICPR-v4-2006-JainCD #using
Pores and Ridges: Fingerprint Matching Using Level 3 Features (AKJ, YC, MD), pp. 477–480.
ICPRICPR-v4-2006-NosratighodsAE #novel #set #using #verification
Speaker Verification Using A Novel Set of Dynamic Features (MN, EA, JE), pp. 266–269.
ICPRICPR-v4-2006-OuyangFSC
Fingerprint Matching With Rotation-Descriptor Texture Features (ZO, JF, FS, AC), pp. 417–420.
ICPRICPR-v4-2006-ReisertB #3d #data-driven #database #integration #invariant #using
Invariant Features for 3D-Data based on Group Integration using Directional Information and Spherical Harmonic Expansion (MR, HB), pp. 206–209.
ICPRICPR-v4-2006-SunY #3d #evaluation #feature model #identification
Evaluation of 3D Facial Feature Selection for Individual Facial Model Identification (YS, LY), pp. 562–565.
ICPRICPR-v4-2006-VillamizarSA #detection #image #invariant #realtime #using
Computation of Rotation Local Invariant Features using the Integral Image for Real Time Object Detection (MV, AS, JAC), pp. 81–85.
ICPRICPR-v4-2006-WuQ #geometry #identification #using
A Hierarchical Palmprint Identification Method Using Hand Geometry and Grayscale Distribution Features (JW, ZQ), pp. 409–412.
ICPRICPR-v4-2006-XuanZCZSF06a #distance #feature model
Feature Selection based on the Bhattacharyya Distance (GX, XZ, PC, ZZ, YQS, DF), p. 957.
ICPRICPR-v4-2006-XuC #classification #invariant #multi
Multiscale Blob Features for Gray Scale, Rotation and Spatial Scale Invariant Texture Classification (QX, YQC), pp. 29–32.
ICPRICPR-v4-2006-YinAC #identification
Combining Cepstral and Prosodic Features in Language Identification (BY, EA, FC), pp. 254–257.
ICPRICPR-v4-2006-ZhangMH #feature model #multi #network
Multiscale Feature Extraction of Finger-Vein Patterns Based on Curvelets and Local Interconnection Structure Neural Network (ZZ, SM, XH), pp. 145–148.
ICPRICPR-v4-2006-ZhouB #distance #recognition #video
Feature Fusion of Face and Gait for Human Recognition at a Distance in Video (XZ, BB), pp. 529–532.
ICPRICPR-v4-2006-ZlatoffRTB #image #retrieval
Content-Based Image Retrieval: on theWay to Object Features (NZ, GR, BT, AB), pp. 153–156.
KDDKDD-2006-BurkeMWB #classification #collaboration #detection #recommendation
Classification features for attack detection in collaborative recommender systems (RDB, BM, CW, RB), pp. 542–547.
KDDKDD-2006-CarvalhoC #feature model #learning #online #performance
Single-pass online learning: performance, voting schemes and online feature selection (VRC, WWC), pp. 548–553.
KDDKDD-2006-MorchenMU #generative #modelling #music #statistics
Understandable models Of music collections based on exhaustive feature generation with temporal statistics (FM, IM, AU), pp. 882–891.
KDDKDD-2006-TsangKK #feature model #kernel #performance #set
Efficient kernel feature extraction for massive data sets (IWT, AK, JTK), pp. 724–729.
KDDKDD-2006-ZhangL #classification #string
Extracting key-substring-group features for text classification (DZ, WSL), pp. 474–483.
KRKR-2006-RandellW #abduction #visual notation
Abductive Visual Perception with Feature Clouds (DAR, MW), pp. 352–361.
KRKR-2006-ThielscherW #calculus #semantics
The Features-and-Fluents Semantics for the Fluent Calculus (MT, TW), pp. 362–370.
SIGIRSIGIR-2006-JeonCLP #framework #predict #quality
A framework to predict the quality of answers with non-textual features (JJ, WBC, JHL, SP), pp. 228–235.
SIGIRSIGIR-2006-LiZZL #case study #comparative #design #experience #library #user interface
A comparative study of the effect of search feature design on user experience in digital libraries (DLs) (YL, XZ, YZ, JL), pp. 669–670.
SIGIRSIGIR-2006-Mu #matter #question #retrieval #semantics #video #visual notation
Content-based video retrieval: does video’s semantic visual feature matter? (XM), pp. 679–680.
SIGIRSIGIR-2006-Mu06a #retrieval #semantics #video #visual notation
Supporting semantic visual feature browsing in contentbased video retrieval (XM), p. 734.
SIGIRSIGIR-2006-SevillanoCAS #clustering #documentation #robust
Feature diversity in cluster ensembles for robust document clustering (XS, GC, FA, JCS), pp. 697–698.
SIGIRSIGIR-2006-TreeratpitukC #automation #case study #clustering #statistics #using
An experimental study on automatically labeling hierarchical clusters using statistical features (PT, JPC), pp. 707–708.
GPCEGPCE-2006-ApelB #aspect-oriented #case study
When to use features and aspects?: a case study (SA, DSB), pp. 59–68.
GPCEGPCE-2006-CzarneckiP #constraints #ocl #verification
Verifying feature-based model templates against well-formedness OCL constraints (KC, KP), pp. 211–220.
GPCEGPCE-2006-Prehofer #composition #multi #reasoning #semantics
Semantic reasoning about feature composition via multiple aspect-weavings (CP), pp. 237–242.
GPCEGPCE-2006-TrujilloBD #multi #product line #refactoring
Feature refactoring a multi-representation program into a product line (ST, DSB, OD), pp. 191–200.
RERE-2006-ChenZZM #analysis #dependence #identification #requirements
Identification of Crosscutting Requirements Based on Feature Dependency Analysis (KC, HZ, WZ, HM), pp. 300–303.
RERE-2006-ReiserW #multi #product line
Managing Highly Complex Product Families with Multi-Level Feature Trees (MOR, MW), pp. 146–155.
RERE-2006-SchobbensHT #bibliography #diagrams #feature model #semantics
Feature Diagrams: A Survey and a Formal Semantics (PYS, PH, JCT), pp. 136–145.
SACSAC-2006-BergerMD #categorisation #email #set
Exploiting partial decision trees for feature subset selection in e-mail categorization (HB, DM, MD), pp. 1105–1109.
SACSAC-2006-CombarroMRD #categorisation #feature model #metric
Angular measures for feature selection in text categorization (EFC, EM, JR, ID), pp. 826–830.
SACSAC-2006-Lindgren #on the
On handling conflicts between rules with numerical features (TL), pp. 37–41.
SACSAC-2006-MontanesCRD #categorisation #feature model #linear #metric
Finding optimal linear measures for feature selection in text categorization (EM, EFC, JR, ID), pp. 861–862.
SACSAC-2006-PechenizkiyPT #feature model #learning #reduction
The impact of sample reduction on PCA-based feature extraction for supervised learning (MP, SP, AT), pp. 553–558.
SACSAC-2006-SoaresB #kernel #parametricity #using
Selecting parameters of SVM using meta-learning and kernel matrix-based meta-features (CS, PB), pp. 564–568.
FSEFSE-2006-GirouxR #detection #testing #using
Detecting increases in feature coupling using regression tests (OG, MPR), pp. 163–174.
ICSEICSE-2006-ApelLS #aspect-oriented #mixin
Aspectual mixin layers: aspects and features in concert (SA, TL, GS), pp. 122–131.
ICSEICSE-2006-Holmes #reuse #scalability
Unanticipated reuse of large-scale software features (RH), pp. 961–964.
ICSEICSE-2006-LiuBL #legacy #refactoring
Feature oriented refactoring of legacy applications (JL, DSB, CL), pp. 112–121.
SPLCSPLC-2006-AsikainenMS #concept #feature model #modelling
A Unified Conceptual Foundation for Feature Modelling (TA, TM, TS), pp. 31–40.
SPLCSPLC-2006-Batory #composition #product line
Feature Modularity in Software Product Lines (DSB), p. 230.
SPLCSPLC-2006-BrownGBSKG #behaviour #embedded #feature model #modelling #product line #weaving
Weaving Behavior into Feature Models for Embedded System Families (TJB, RG, RB, ITAS, PK, CG), pp. 52–64.
SPLCSPLC-2006-CzarneckiKK #feature model #modelling #ontology
Feature Models are Views on Ontologies (KC, CHPK, KTK), pp. 41–51.
SPLCSPLC-2006-LeeK #approach #configuration management #feature model #product line
A Feature-Oriented Approach to Developing Dynamically Reconfigurable Products in Product Line Engineering (JL, KCK), pp. 131–140.
SPLCSPLC-2006-LeeKKP #analysis #aspect-oriented #development #feature model #product line #programming
Combining Feature-Oriented Analysis and Aspect-Oriented Programming for Product Line Asset Development (KL, KCK, MK, SP), pp. 103–112.
SPLCSPLC-2006-SpinczykP #feature model #modelling #using
Using Feature Models for Product Derivation (OS, HP), p. 225.
WICSAWICSA-2005-BrownBGSK #architecture #development #embedded #product line
Feature-Guided Architecture Development for Embedded System Families (TJB, RB, CG, ITAS, PK), pp. 223–226.
ASEASE-2005-KoschkeQ #feature model #on the
On dynamic feature location (RK, JQ), pp. 86–95.
DocEngDocEng-2005-BeheraLI #documentation #identification
Influence of fusion strategies on feature-based identification of low-resolution documents (AB, DL, RI), pp. 20–22.
DRRDRR-2005-ChenD #feature model #verification
Sequence-matching-based feature extraction with applications to signature verification (YC, XD), pp. 76–83.
ICDARICDAR-2005-BaiH #case study #online #recognition
A Study On the Use of 8-Directional Features For Online Handwritten Chinese Character Recognition (ZLB, QH), pp. 262–266.
ICDARICDAR-2005-ChenS #verification
Use of Exterior Contours and Shape Features in Off-line Signature Verification (SC, SNS), pp. 1280–1284.
ICDARICDAR-2005-El-HajjLM #markov #modelling #recognition #using
Arabic Handwriting Recognition Using Baseline Dependant Features and Hidden Markov Modeling (REH, LLS, CM), pp. 893–897.
ICDARICDAR-2005-FinkP #feature model #independence #on the #recognition
On Appearance-Based Feature Extraction Methods for Writer-Independent Handwritten Text Recognition (GAF, TP), pp. 1070–1074.
ICDARICDAR-2005-HaritJC #geometry #graph #image #independence #representation #retrieval #word
Improved Geometric Feature Graph: A Script Independent Representation of Word Images for Compression, and Retrieval (GH, RJ, SC), pp. 421–425.
ICDARICDAR-2005-IwamuraNOA #recognition
Isolated Character Recognition by Searching Feature Points (MI, KN, SO, HA), pp. 1035–1039.
ICDARICDAR-2005-KangG #ranking #recognition
A New Feature Ranking Method in a HMM-Based Handwriting Recognition System (SK, VG), pp. 779–783.
ICDARICDAR-2005-LiuD #classification #multi #polynomial #recognition #using
Handwritten Character Recognition Using Gradient Feature and Quadratic Classifier with Multiple Discrimination Schemes (HL, XD), pp. 19–25.
ICDARICDAR-2005-LiuFZL #documentation #image #retrieval
Document Image Retrieval Based on Density Distribution Feature and Key Block Feature (HL, SF, HZ, XL), pp. 1040–1044.
ICDARICDAR-2005-LiuKF #comparison #feature model #recognition
Gabor Feature Extraction for Character Recognition: Comparison with Gradient Feature (CLL, MK, HF), pp. 121–125.
ICDARICDAR-2005-LiuMK #classification #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 #classification #detection #image
Text Detection in Images Based on Unsupervised Classification of Edge-based Features (CL, CW, RD), pp. 610–614.
ICDARICDAR-2005-MethasateMST #recognition
The feature Combination Technique for Off-line Thai Character Recognition System (IM, SM, SSt, TT), pp. 1006–1009.
ICDARICDAR-2005-OkumurUS #coordination #implementation #online #recognition
An HMM Implementation for On-line Handwriting Recognition — Based on Pen-Coordinate Feature and Pen-Direction Feature (DO, SU, HS), pp. 26–30.
ICDARICDAR-2005-RadtkeSW #classification #feature model
Intelligent Feature Extraction for Ensemble of Classifiers (PVWR, RS, TW), pp. 866–870.
ICDARICDAR-2005-RichiardiKD #feature model #online #verification
Local and Global Feature Selection for On-line Signature Verification (JR, HK, AD), pp. 625–629.
ICDARICDAR-2005-SaoiGK #clustering #detection #image #multi
Text Detection in Color Scene Images based on Unsupervised Clustering of Multi-channel Wavelet Features (TS, HG, HK), pp. 690–694.
ICDARICDAR-2005-SchlapbachKB #feature model #identification
ImprovingWriter Identification by Means of Feature Selection and Extraction (AS, VK, HB), pp. 131–135.
ICDARICDAR-2005-SunHKN #recognition #using
Camera based Degraded Text Recognition Using Grayscale Feature (JS, YH, YK, SN), pp. 182–186.
ICDARICDAR-2005-TerradesV
Local Norm Features based on ridgelets Transform (ORT, EV), pp. 700–704.
ICDARICDAR-2005-ZhangBS #feature model #hybrid #recognition
Hybrid Feature Extraction and Feature Selection for Improving Recognition Accuracy of Handwritten Numerals (PZ, TDB, CYS), pp. 136–140.
FASEFASE-2005-HammoudaHPK #using #variability
Managing Variability Using Heterogeneous Feature Variation Patterns (IH, JH, MP, KK), pp. 145–159.
CSMRCSMR-2005-GreevyD #analysis #approach #correlation #using
Correlating Features and Code Using a Compact Two-Sided Trace Analysis Approach (OG, SD), pp. 314–323.
ICSMEICSM-2005-AntoniolG #approach #case study #identification #novel
Feature Identification: A Novel Approach and a Case Study (GA, YGG), pp. 357–366.
ICSMEICSM-2005-EisenbergV
Dynamic Feature Traces: Finding Features in Unfamiliar Code (ADE, KDV), pp. 337–346.
ICSMEICSM-2005-GreevyDG #analysis #evolution #semantics
Analyzing Feature Traces to Incorporate the Semantics of Change in Software Evolution Analysis (OG, SD, TG), pp. 347–356.
ICSMEICSM-2005-MarcusR #concept #identification #source code
Identifications of Concepts, Features, and Concerns in Source Code (AM, VR), p. 718.
CHICHI-2005-BeckwithBWCSH #debugging #effectiveness #gender #question
Effectiveness of end-user debugging software features: are there gender issues? (LB, MMB, SW, CRC, SS, MH), pp. 869–878.
CHICHI-2005-RosenholtzLMJ
Feature congestion: a measure of display clutter (RR, YL, JM, ZJ), pp. 761–770.
VISSOFTVISSOFT-2005-GreevyLW #3d #feature model #interactive #visualisation
Visualizing Feature Interaction in 3-D (OG, ML, CW), pp. 114–119.
VISSOFTVISSOFT-2005-SmithM #identification #interactive #java #runtime #source code
Identifying Structural Features of Java Programs by Analysing the Interaction of Classes at Runtime (MPS, MM), pp. 108–113.
AdaEuropeAdaEurope-2005-Brosgol #ada #comparison #java #realtime #specification
A Comparison of the Mutual Exclusion Features in Ada and the Real-Time Specification for Java TM (BMB), pp. 129–143.
CAiSECAiSE-2005-BenavidesTC #automation #feature model #modelling #reasoning
Automated Reasoning on Feature Models (DB, PTMA, ARC), pp. 491–503.
ICEISICEIS-v1-2005-ArandaVCP #elicitation #tool support
Choosing Groupware Tools and Elicitation Techniques According to Stakeholders’ Features (GNA, AV, AC, MP), pp. 68–75.
CIKMCIKM-2005-HanK #recommendation
Feature-based recommendation system (EHH, GK), pp. 446–452.
CIKMCIKM-2005-KanT #classification #performance #using
Fast webpage classification using URL features (MYK, HONT), pp. 325–326.
CIKMCIKM-2005-RamirezWV #retrieval #xml
Structural features in content oriented XML retrieval (GR, TW, APdV), pp. 291–292.
ECIRECIR-2005-ChenDWLZ #feature model
AP-Based Borda Voting Method for Feature Extraction in TRECVID-2004 (LC, DD, DW, FL, BZ), pp. 568–570.
ECIRECIR-2005-RuchPS
Features Combination for Extracting Gene Functions from MEDLINE (PR, LP, JS), pp. 112–126.
ICMLICML-2005-GlocerET #classification #feature model #online
Online feature selection for pixel classification (KAG, DE, JT), pp. 249–256.
ICMLICML-2005-Keerthi #classification #effectiveness #feature model
Generalized LARS as an effective feature selection tool for text classification with SVMs (SSK), pp. 417–424.
KDDKDD-2005-FujimakiYM #approach #detection #kernel #problem #using
An approach to spacecraft anomaly detection problem using kernel feature space (RF, TY, KM), pp. 401–410.
KDDKDD-2005-JinZM #collaboration #recommendation #web
A maximum entropy web recommendation system: combining collaborative and content features (XJ, YZ, BM), pp. 612–617.
KDDKDD-2005-LazarevicK #detection
Feature bagging for outlier detection (AL, VK), pp. 157–166.
KDDKDD-2005-Momma #kernel #performance #scalability
Efficient computations via scalable sparse kernel partial least squares and boosted latent features (MM), pp. 654–659.
KDDKDD-2005-ZhouFSU #feature model #streaming #using
Streaming feature selection using alpha-investing (JZ, DPF, RAS, LHU), pp. 384–393.
MLDMMLDM-2005-Bak #classification #linear #multi
A New Multidimensional Feature Transformation for Linear Classifiers and Its Applications (EB), pp. 275–284.
MLDMMLDM-2005-Bobrowski #feature model #modelling
Ranked Modelling with Feature Selection Based on the CPL Criterion Functions (LB), pp. 218–227.
MLDMMLDM-2005-HanCY #analysis #component #feature model #image #independence #using
Aquaculture Feature Extraction from Satellite Image Using Independent Component Analysis (JGH, KHC, YKY), pp. 660–666.
MLDMMLDM-2005-KurganH #approach #feature model #predict #sequence
Prediction of Secondary Protein Structure Content from Primary Sequence Alone — A Feature Selection Based Approach (LAK, LH), pp. 334–345.
MLDMMLDM-2005-LegrandN #feature model #using
Feature Selection Method Using Preferences Aggregation (GL, NN), pp. 203–217.
MLDMMLDM-2005-MakrehchiK #classification #using
Text Classification Using Small Number of Features (MM, MSK), pp. 580–589.
MLDMMLDM-2005-ScalzoP #learning #visual notation
Unsupervised Learning of Visual Feature Hierarchies (FS, JHP), pp. 243–252.
SEKESEKE-2005-BenavidesTC #constraints #feature model #modelling #programming #using
Using Constraint Programming to Reason on Feature Models (DB, PT, ARC), pp. 677–682.
SEKESEKE-2005-LiCLY #analysis #design #evolution #feature model #legacy #using
Using Feature-Oriented Analysis to Recover Legacy Software Design for Software Evolution (SL, FC, ZL, HY), pp. 336–341.
SEKESEKE-2005-MorenoS #human-computer #usability
Helping Software Engineers to Incorporate HCI Usability Features (AMM, MISS), pp. 719–726.
SEKESEKE-2005-YeS #dependence #modelling #variability
Modelling Feature Variability and Dependency in Two Views (HY, AS), pp. 661–664.
SIGIRSIGIR-2005-LiY #analysis #recursion
Analysis of recursive feature elimination methods (FL, YY), pp. 633–634.
SIGIRSIGIR-2005-YanLZYCCFM #categorisation #feature model #named #orthogonal
OCFS: optimal orthogonal centroid feature selection for text categorization (JY, NL, BZ, SY, ZC, QC, WF, WYM), pp. 122–129.
ECMFAECMDA-FA-2005-HwanKC #feature model #modelling
Synchronizing Cardinality-Based Feature Models and Their Specializations (CHPK, KC), pp. 331–348.
MODELSMoDELS-2005-ZhangMZY #approach #component #feature model
Transformation from CIM to PIM: A Feature-Oriented Component-Based Approach (WZ, HM, HZ, JY), pp. 248–263.
MODELSMoDELS-2005-ZhangMZY #approach #component #feature model
Transformation from CIM to PIM: A Feature-Oriented Component-Based Approach (WZ, HM, HZ, JY), pp. 248–263.
ECOOPECOOP-2005-Lopez-HerrejonBC #composition
Evaluating Support for Features in Advanced Modularization Technologies (RELH, DSB, WRC), pp. 169–194.
GPCEGPCE-2005-ApelLRS #aspect-oriented #feature model #programming
FeatureC++: On the Symbiosis of Feature-Oriented and Aspect-Oriented Programming (SA, TL, MR, GS), pp. 125–140.
GPCEGPCE-2005-CzarneckiA #approach #modelling
Mapping Features to Models: A Template Approach Based on Superimposed Variants (KC, MA), pp. 422–437.
RERE-2005-BittnerBPRW #requirements #reuse #scalability #variability
Managing Variability and Reuse of Features and Requirements for Large and Complex Organizational Structures (MB, AB, AP, MOR, MW), pp. 469–470.
RERE-2005-ChenZZM #approach #clustering #feature model #modelling #requirements
An Approach to Constructing Feature Models Based on Requirements Clustering (KC, WZ, HZ, HM), pp. 31–40.
RERE-2005-ZhangMZ #approach #dependence #feature model #modelling #requirements
A Feature-Oriented Approach to Modeling Requirements Dependencies (WZ, HM, HZ), pp. 273–284.
SACSAC-2005-BustosKS
A pivot-based index structure for combination of feature vectors (BB, DAK, TS), pp. 1180–1184.
SACSAC-2005-LiY #classification #predict #recursion #using
Using recursive classification to discover predictive features (FL, YY), pp. 1054–1058.
SACSAC-2005-RahalRPNPRV #biology #incremental #interactive #mining
Incremental interactive mining of constrained association rules from biological annotation data with nominal features (IR, DR, AP, HN, WP, RR, WVG), pp. 123–127.
GTTSEGTTSE-2005-Batory #programming #tutorial
A Tutorial on Feature Oriented Programming and the AHEAD Tool Suite (DSB), pp. 3–35.
GTTSEGTTSE-2005-BenavidesSMC #analysis #automation #csp #feature model #java #modelling #using
Using Java CSP Solvers in the Automated Analyses of Feature Models (DB, SS, PTMA, ARC), pp. 399–408.
GTTSEGTTSE-2005-PorkolabZ #c++ #composition #metaprogramming #problem
A Feature Composition Problem and a Solution Based on C++ Template Metaprogramming (ZP, IZ), pp. 459–470.
SPLCSPLC-2005-Batory #feature model #modelling
Feature Models, Grammars, and Propositional Formulas (DSB), pp. 7–20.
SPLCSPLC-2005-ErikssonBB #approach #case study #domain model #modelling
The PLUSS Approach — Domain Modeling with Features, Use Cases and Use Case Realizations (ME, JB, KB), pp. 33–44.
SPLCSPLC-2005-KangKLK #case study #feature model #legacy #product line #re-engineering
Feature-Oriented Re-engineering of Legacy Systems into Product Line Assets — a Case Study (KCK, MK, JL, BK), pp. 45–56.
SPLCSPLC-2005-MassenL #feature model #modelling
Determining the Variation Degree of Feature Models (TvdM, HL), pp. 82–88.
ICTSSTestCom-2005-ChiH #communication #detection #generative #interactive #testing
Test Generation for Interaction Detection in Feature-Rich Communication Systems (CC, RH), pp. 242–257.
DATEDATE-v1-2004-MetraMO #design #fault #question #testing
Are Our Design for Testability Features Fault Secure? (CM, TMM, MO), pp. 714–715.
DRRDRR-2004-ZhangSH #image #retrieval #using #word
Word image retrieval using binary features (BZ, SNS, CH), pp. 45–53.
CSMRCSMR-2004-PashovRP #architecture #feature model #modelling
Supporting Architectural Restructuring by Analyzing Feature Models (IP, MR, IP), pp. 25–36.
ICSMEICSM-2004-LuciaFOT #traceability
Enhancing an Artefact Management System with Traceability Recovery Features (ADL, FF, RO, GT), pp. 306–315.
ICSMEICSM-2004-SalahM
A Hierarchy of Dynamic Software Views: From Object-Interactions to Feature-Interactions (MS, SM), pp. 72–81.
ICSMEICSM-2004-ZhaoZHMS #algorithm #feature model #scalability
Alternative Scalable Algorithms for Lattice-Based Feature Location (WZ, LZ, DH, HM, JS), p. 528.
ICEISICEIS-v3-2004-Raabe #modelling #re-engineering
Feature Matching in Model-Based Software Engineering (AR), pp. 163–172.
CIKMCIKM-2004-AghiliAA #geometry #using
Protein structure alignment using geometrical features (SAA, DA, AEA), pp. 148–149.
CIKMCIKM-2004-WangL #categorisation #feature model
Feature selection with conditional mutual information maximin in text categorization (GW, FHL), pp. 342–349.
ECIRECIR-2004-BelkhatirMC #automation #concept #image #multi #retrieval
Integrating Perceptual Signal Features within a Multi-facetted Conceptual Model for Automatic Image Retrieval (MB, PM, YC), pp. 267–282.
ECIRECIR-2004-MoschittiB #classification
Complex Linguistic Features for Text Classification: A Comprehensive Study (AM, RB), pp. 181–196.
ICMLICML-2004-AppiceCRF #multi #problem
Redundant feature elimination for multi-class problems (AA, MC, SR, PAF).
ICMLICML-2004-BahamondeBDQLCAG #case study #learning #set
Feature subset selection for learning preferences: a case study (AB, GFB, JD, JRQ, OL, JJdC, JA, FG).
ICMLICML-2004-Forman #classification #feature model #multi
A pitfall and solution in multi-class feature selection for text classification (GF).
ICMLICML-2004-GabrilovichM #categorisation #feature model #using
Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5 (EG, SM).
ICMLICML-2004-Gilad-BachrachNT #algorithm #feature model
Margin based feature selection — theory and algorithms (RGB, AN, NT).
ICMLICML-2004-HardinTA #feature model #linear
A theoretical characterization of linear SVM-based feature selection (DPH, IT, CFA).
ICMLICML-2004-Jebara #kernel #multi
Multi-task feature and kernel selection for SVMs (TJ).
ICMLICML-2004-JinL #induction #robust
Robust feature induction for support vector machines (RJ, HL).
ICMLICML-2004-KimK #feature model
Gradient LASSO for feature selection (YK, JK).
ICMLICML-2004-YeJLP #analysis #feature model #linear
Feature extraction via generalized uncorrelated linear discriminant analysis (JY, RJ, QL, HP).
ICPRICPR-v1-2004-BariamisIMK #architecture #feature model #image #realtime
An FPGA-Based Architecture for Real Time Image Feature Extraction (DGB, DKI, DEM, SAK), pp. 801–804.
ICPRICPR-v1-2004-ClausiD #image #segmentation
Feature Fusion for Image Texture Segmentation (DAC, HD), pp. 580–583.
ICPRICPR-v1-2004-FanWLT #null #recognition
Combining Null Space-based Gabor Features for Face Recognition (WF, YW, WL, TT), pp. 330–333.
ICPRICPR-v1-2004-GunterB #evaluation #feature model #recognition #word
An Evaluation of Ensemble Methods in Handwritten Word Recognition Based on Feature Selection (SG, HB), pp. 388–392.
ICPRICPR-v1-2004-HallOC #detection #low level
A Trainable Low-level Feature Detector (PMH, MO, JPC), pp. 708–711.
ICPRICPR-v1-2004-KokareBC #image #retrieval
Rotated Complex Wavelet based Texture Features for Content Based Image Retrieval (MK, PKB, BNC), pp. 652–655.
ICPRICPR-v1-2004-KolschKNP #classification #image
Enhancements for Local Feature Based Image Classification (TK, DK, HN, RP), pp. 248–251.
ICPRICPR-v1-2004-LiHS #feature model #image #programming #retrieval #search-based #semantics #using
Semantic Feature Extraction Using Genetic Programming in Image Retrieval (QL, HH, ZS), pp. 648–651.
ICPRICPR-v1-2004-NammalwarGW #integration #segmentation
Integration of Feature Distributions for Colour Texture Segmentation (PN, OG, PFW), pp. 716–719.
ICPRICPR-v1-2004-PnevmatikakisP #comparison
Comparison of Eigenface-Based Feature Vectors under Different Impairments (AP, LP), pp. 296–299.
ICPRICPR-v1-2004-Rivero-MorenoB #feature model
Texture Feature Extraction and Indexing by Hermite Filters (CJRM, SB), pp. 684–687.
ICPRICPR-v1-2004-ShanGCCY #bibliography #recognition #robust
Review the Strength of Gabor Features for Face Recognition from the Angle of Its Robustness to Mis-Alignment (SS, WG, YC, BC, PY), pp. 338–341.
ICPRICPR-v1-2004-SochmanM
Inter-Stage Feature Propagation in Cascade Building with AdaBoost (JS, JM), pp. 236–239.
ICPRICPR-v1-2004-WuAL #detection
Glasses Detection by Boosting Simple Wavelet Features (BW, HA, RL), pp. 292–295.
ICPRICPR-v1-2004-XuC #classification #statistics
Statistical Landscape Features for Texture Classification (CLX, YQC), pp. 676–679.
ICPRICPR-v1-2004-ZhouT #analysis #clustering #coordination #documentation #geometry #re-engineering #visual notation
Coordinate Systems Reconstruction for Graphical Documents by Hough-feature Clustering and Geometric Analysis (YPZ, CLT), pp. 376–379.
ICPRICPR-v2-2004-BeierholmB #music #speech #using
Speech Music Discrimination Using Class-Specific Features (TB, PMB), pp. 379–382.
ICPRICPR-v2-2004-ChenLF #adaptation #feature model #probability
Probabilistic Tracking with Adaptive Feature Selection (HTC, TLL, CSF), pp. 736–739.
ICPRICPR-v2-2004-DongB #database #image #modelling
Discriminant Features for Model-Based Image Databases (AD, BB), pp. 997–1000.
ICPRICPR-v2-2004-FarmerBJ #feature model #random #scalability #using
Large Scale Feature Selection Using Modified Random Mutation Hill Climbing (MEF, SB, AKJ), pp. 287–290.
ICPRICPR-v2-2004-HaasdonkHB #invariant
Adjustable Invariant Features by Partial Haar-Integration (BH, AH, HB), pp. 769–774.
ICPRICPR-v2-2004-JunejoJS #modelling #multi #video
Multi Feature Path Modeling for Video Surveillance (INJ, OJ, MS), pp. 716–719.
ICPRICPR-v2-2004-KaplanRS #image #robust
Robust Feature Matching Across Widely Separated Color Images (AK, ER, IS), pp. 136–139.
ICPRICPR-v2-2004-KherfiBZ #effectiveness #image #retrieval #semantics #visual notation
Combining Visual Features with Semantics for a More Effective Image Retrieval (MLK, DB, DZ), pp. 961–964.
ICPRICPR-v2-2004-KimBSCCKC #image #using #verification
Scene Text Extraction in Natural Scene Images using Hierarchical Feature Combining and Verification (KCK, HRB, YJS, YWC, SYC, KKK, YC), pp. 679–682.
ICPRICPR-v2-2004-LeungNL #classification
ICA-FX Features for Classification of Singing Voice and Instrumental Sound (TWL, CWN, RWHL), pp. 367–370.
ICPRICPR-v2-2004-LillholmP #classification
Jet Based Feature Classification (ML, KSP), pp. 787–790.
ICPRICPR-v2-2004-LiuS #learning
Reinforcement Learning-Based Feature Learning for Object Tracking (FL, JS), pp. 748–751.
ICPRICPR-v2-2004-MitraM #clustering #feature model
Feature Selection and Gene Clustering from Gene Expression Data (PM, DDM), pp. 343–346.
ICPRICPR-v2-2004-MozaffarifK #classification #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-Nagao #approach #feature model #kernel
Bayesian Approach with Nonlinear Kernels to Feature Extraction (KN), pp. 153–156.
ICPRICPR-v2-2004-PlotzF #analysis #biology #feature model #sequence
Feature Extraction for Improved Profile HMM based Biological Sequence Analysis (TP, GAF), pp. 315–318.
ICPRICPR-v2-2004-SerbyKG #multi #probability #using
Probabilistic Object Tracking Using Multiple Features (DS, EKM, LJVG), pp. 184–187.
ICPRICPR-v2-2004-ShihL #analysis #detection #using #video
Face Detection Using Discriminating Feature Analysis and Support Vector Machine in Video (PS, CL), pp. 407–410.
ICPRICPR-v2-2004-ShimanoN #optimisation #recognition
Simultaneous Optimization of Class Configuration and Feature Space for Object Recognition (MS, KN), pp. 7–10.
ICPRICPR-v2-2004-StefanoGM #approach #feature model #multi #online #segmentation
A Multiresolution Approach to On-line Handwriting Segmentation and Feature Extraction (CDS, MG, AM), pp. 614–617.
ICPRICPR-v2-2004-TahirBKA #classification #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-WilsonH #distance #graph
Levenshtein Distance for Graph Spectral Features (RCW, ERH), pp. 489–492.
ICPRICPR-v2-2004-Wohler #3d #re-engineering #self
3D Surface Reconstruction by Self-Consistent Fusion of Shading and Shadow Features (CW), pp. 204–207.
ICPRICPR-v2-2004-XuanDKHCW #feature model #multi #predict #profiling #robust
Robust Feature Selection by Weighted Fisher Criterion for Multiclass Prediction in Gene Expression Profiling (JX, YD, JIK, EPH, RC, YJW), pp. 291–294.
ICPRICPR-v2-2004-ZhangLG #detection #realtime #using
Real-Time Face Detection Using Boosting in Hierarchical Feature Spaces (DZ, SZL, DGP), pp. 411–414.
ICPRICPR-v3-2004-CarneiroJ #using
Pruning Local Feature Correspondences Using Shape Context (GC, ADJ), pp. 16–19.
ICPRICPR-v3-2004-DornaikaD #online
Online Appearance-Based Face and Facial Feature Tracking (FD, FD), pp. 814–817.
ICPRICPR-v3-2004-FusseneggerOPA #detection #recognition #segmentation #using
Object Recognition Using Segmentation for Feature Detection (MF, AO, AP, PA), pp. 41–44.
ICPRICPR-v3-2004-KashinoKK #clustering #video
A Quick Video Search Method based on Local and Global Feature Clustering (KK, AK, TK), pp. 894–897.
ICPRICPR-v3-2004-LiewWY #classification #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-MiyoshiLKYN #automation #geometry
Automatic Extraction of Buildings Utilizing Geometric Features of a Scanned Topographic Map (TM, WL, KK, HY, EN), pp. 626–629.
ICPRICPR-v3-2004-SalbergH #estimation #segmentation #using
Object Segmentation and Feature Estimation Using Shadows (ABS, AH), pp. 674–678.
ICPRICPR-v3-2004-WangLL #analysis #towards
Tensor Voting Toward Feature Space Analysis (JW, HL, QL), pp. 462–465.
ICPRICPR-v3-2004-WanX #automation #generative #multimodal #performance
Efficient Multimodal Features for Automatic Soccer Highlight Generation (KW, CX), pp. 973–976.
ICPRICPR-v3-2004-WuZZ #feature model #linear #using
Relevant Linear Feature Extraction Using Side-information and Unlabeled Data (FW, YZ, CZ), pp. 582–585.
ICPRICPR-v3-2004-ZhouK04a #classification
The Pattern Classification Based on the Nearest Feature Midpoints (ZZ, CKK), pp. 446–449.
ICPRICPR-v4-2004-CastanedaLC #architecture #composition #implementation #realtime #visual notation
Implementation of a Modular Real-Time Feature-Based Architecture Applied to Visual Face Tracking (BC, YL, JCC), pp. 167–170.
ICPRICPR-v4-2004-KoseckaY #estimation #invariant #locality
Global Localization and Relative Pose Estimation Based on Scale-Invariant Features (JK, XY), pp. 319–322.
ICPRICPR-v4-2004-MarkouS #feature model
Feature Selection based on a Black Hole Model of Data Reorganization (MM, SS), pp. 565–568.
ICPRICPR-v4-2004-PaclikVD #algorithm #feature model #multi
Multi-Class Extensions of the GLDB Feature Extraction Algorithm for Spectral Data (PP, SV, RPWD), pp. 629–632.
ICPRICPR-v4-2004-PrasadSK #image #set #using
Feature Subset Selection using ICA for Classifying Emphysema in HRCT Images (MNP, AS, IK), pp. 515–518.
ICPRICPR-v4-2004-Qiu #clustering #image
Image and Feature Co-Clustering (GQ), pp. 991–994.
ICPRICPR-v4-2004-SawanoO #difference
Road Extraction by Snake with Inertia and Differential Features (HS, MO), pp. 380–383.
ICPRICPR-v4-2004-WuWZ #energy #recognition #using
Palmprint Recognition Using Directional Line Energy Feature (XW, KW, DZ), pp. 475–478.
ICPRICPR-v4-2004-Xiao-JunKYMW #algorithm #feature model #recognition
A New Direct LDA (D-LDA) Algorithm for Feature Extraction in Face Recognition (XW, JK, JYY, KM, SW), pp. 545–548.
ICPRICPR-v4-2004-YangL #detection #multi
Multiple Pedestrian Detection and Tracking based on Weighted Temporal Texture Features (HDY, SWL), pp. 248–251.
ICPRICPR-v4-2004-YangSW #multi #people
People Tracking by Integrating Multiple Features (MTY, YCS, SCW), pp. 929–932.
ICPRICPR-v4-2004-YingH04a #detection #using
Catadioptric Line Features Detection using Hough Transform (XY, ZH), pp. 839–842.
ICPRICPR-v4-2004-ZhaiRS