62 papers:
DAC-2015-CavigelliMB #embedded #network #realtime- Accelerating real-time embedded scene labeling with convolutional networks (LC, MM, LB), p. 6.
DATE-2015-0001B #clustering #energy #manycore #performance- A ultra-low-energy convolution engine for fast brain-inspired vision in multicore clusters (FC, LB), pp. 683–688.
ECIR-2015-HuynhHR #analysis #learning #sentiment #strict- Learning Higher-Level Features with Convolutional Restricted Boltzmann Machines for Sentiment Analysis (TH, YH, SMR), pp. 447–452.
ICML-2015-ClarkS #game studies #network- Training Deep Convolutional Neural Networks to Play Go (CC, AJS), pp. 1766–1774.
ICML-2015-HongYKH #learning #network #online- Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network (SH, TY, SK, BH), pp. 597–606.
SIGIR-2015-SeverynM #learning #network #rank- Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks (AS, AM), pp. 373–382.
SIGIR-2015-SeverynM15a #analysis #network #sentiment #twitter- Twitter Sentiment Analysis with Deep Convolutional Neural Networks (AS, AM), pp. 959–962.
CASE-2014-LinHC #gesture #network #recognition #using- Human hand gesture recognition using a convolution neural network (HIL, MHH, WKC), pp. 1038–1043.
CIKM-2014-ShenHGDM #information retrieval #semantics- A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval (YS, XH, JG, LD, GM), pp. 101–110.
ICML-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.
ICML-c1-2014-PinheiroC #network- Recurrent Convolutional Neural Networks for Scene Labeling (PHOP, RC), pp. 82–90.
ICML-c1-2014-ZhouT #generative #network #predict #probability- Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction (JZ, OGT), pp. 745–753.
ICPR-2014-DongPHLDJ #classification #network #using- Vehicle Type Classification Using Unsupervised Convolutional Neural Network (ZD, MP, YH, TL, YD, YJ), pp. 172–177.
ICPR-2014-HafemannOC #network #recognition #using- Forest Species Recognition Using Deep Convolutional Neural Networks (LGH, LSO, PRC), pp. 1103–1107.
ICPR-2014-KangKYLD #classification #documentation #image #network- Convolutional Neural Networks for Document Image Classification (LK, JK, PY, YL, DSD), pp. 3168–3172.
ICPR-2014-NieKZ #learning #recognition #using- Periocular Recognition Using Unsupervised Convolutional RBM Feature Learning (LN, AK, SZ), pp. 399–404.
ICPR-2014-RenYZH #classification #image #learning #nearest neighbour- Learning Convolutional Nonlinear Features for K Nearest Neighbor Image Classification (WR, YY, JZ, KH), pp. 4358–4363.
ICPR-2014-SuLTLT #recognition #using- Character Recognition in Natural Scenes Using Convolutional Co-occurrence HOG (BS, SL, ST, JHL, CLT), pp. 2926–2931.
ICPR-2014-WuHYWT #image #network #segmentation- Early Hierarchical Contexts Learned by Convolutional Networks for Image Segmentation (ZW, YH, YY, LW, TT), pp. 1538–1543.
SAC-2014-MoonKSP #image #novel #scalability- A novel double linear-cubic convolution interpolation for digital image scaling (HMM, KRK, JS, SBP), pp. 1733–1734.
ICDAR-2013-BlucheNK #feature model #network #recognition #word- Feature Extraction with Convolutional Neural Networks for Handwritten Word Recognition (TB, HN, CK), pp. 285–289.
ICDAR-2013-CecottiV13a #multi #recognition- A Radial Neural Convolutional Layer for Multi-oriented Character Recognition (HC, SV), pp. 668–672.
ICDAR-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.
ICML-c1-2013-KarbasiSS #learning- Iterative Learning and Denoising in Convolutional Neural Associative Memories (AK, AHS, AS), pp. 445–453.
ICPR-2012-LinnerS #comparison #normalisation #quality #using- Comparison of restoration quality on square and hexagonal grids using normalized convolution (EL, RS), pp. 3046–3049.
ICPR-2012-SermanetCL #classification #network- Convolutional neural networks applied to house numbers digit classification (PS, SC, YL), pp. 3288–3291.
ICPR-2012-WangWCN #network #recognition- End-to-end text recognition with convolutional neural networks (TW, DJW, AC, AYN), pp. 3304–3308.
ICPR-2012-WuFH0N #network #recognition- Cascaded heterogeneous convolutional neural networks for handwritten digit recognition (CW, WF, YH, JS, SN), pp. 657–660.
ICPR-2012-ZhangW #image #segmentation- An image fusion method based on region segmentation and Cauchy convolution (YQZ, XJW), pp. 392–395.
KDD-2012-0001LHSE #approach #towards- Towards heterogeneous temporal clinical event pattern discovery: a convolutional approach (FW, NL, JH, JS, SE), pp. 453–461.
ICDAR-2011-BukhariSB #set #using- Text-Line Extraction Using a Convolution of Isotropic Gaussian Filter with a Set of Line Filters (SSB, FS, TMB), pp. 579–583.
ICDAR-2011-CiresanMGS #classification #network- Convolutional Neural Network Committees for Handwritten Character Classification (DCC, UM, LMG, JS), pp. 1135–1139.
ICALP-v1-2011-CliffordJ #bound #integer #multi #online- Lower Bounds for Online Integer Multiplication and Convolution in the Cell-Probe Model (RC, MJ), pp. 593–604.
CIKM-2011-CroceMB #dependence #kernel #semantics- Semantic convolution kernels over dependency trees: smoothed partial tree kernel (DC, AM, RB), pp. 2013–2016.
ICML-2011-ChenPSDC #analysis #learning #process- The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning (BC, GP, GS, DBD, LC), pp. 361–368.
ICML-2010-JiXYY #3d #network #recognition- 3D Convolutional Neural Networks for Human Action Recognition (SJ, WX, MY, KY), pp. 495–502.
ICPR-2010-DengSS #detection #network #pattern matching #pattern recognition #recognition- Applying Error-Correcting Output Coding to Enhance Convolutional Neural Network for Target Detection and Pattern Recognition (HD, GS, CYS), pp. 4291–4294.
ICPR-2010-Perez-CarrascoSASL #network #realtime- Spike-Based Convolutional Network for Real-Time Processing (JAPC, CS, BA, TSG, BLB), pp. 3085–3088.
HPDC-2010-DiasBG- CUDA-based triangulations of convolution molecular surfaces (SD, KB, AJPG), pp. 531–540.
ICDAR-2009-DengSS #network #recognition- Error-Correcting Output Coding for the Convolutional Neural Network for Optical Character Recognition (HD, GS, CYS), pp. 581–585.
ICML-2009-LeeGRN #learning #network #scalability- Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations (HL, RBG, RR, AYN), pp. 609–616.
DATE-2008-VogtW #configuration management #set- A Reconfigurable Application Specific Instruction Set Processor for Convolutional and Turbo Decoding in a SDR Environment (TV, NW), pp. 38–43.
IFL-2008-Hinze #proving #theorem- Scans and Convolutions — A Calculational Proof of Moessner’s Theorem (RH), pp. 1–24.
ICML-2008-ShiBY #learning #modelling #using- Data spectroscopy: learning mixture models using eigenspaces of convolution operators (TS, MB, BY), pp. 936–943.
ICML-2008-ShinK #kernel- A generalization of Haussler’s convolution kernel: mapping kernel (KS, TK), pp. 944–951.
STOC-2007-BjorklundHKK #fourier #performance #set- Fourier meets möbius: fast subset convolution (AB, TH, PK, MK), pp. 67–74.
TLCA-2007-Vaux #λ-calculus #μ-calculus- Convolution λμ-Calculus (LV), pp. 381–395.
ICPR-v1-2006-KimC #ambiguity #clustering #permutation- ICA-Based Clustering for Resolving Permutation Ambiguity in Frequency-Domain Convolutive Source Separation (MK, SC), pp. 950–954.
ICPR-v3-2006-ChenHWJF #detection #network- The Application of a Convolution Neural Network on Face and License Plate Detection (YNC, CCH, CTW, BSJ, KCF), pp. 552–555.
ICPR-v4-2006-NeuhausB #graph #kernel- A Convolution Edit Kernel for Error-tolerant Graph Matching (MN, HB), pp. 220–223.
ICPR-v4-2006-TiviveB #classification #gender #network- A Shunting Inhibitory Convolutional Neural Network for Gender Classification (FHCT, AB), pp. 421–424.
ICDAR-2005-CecottiB #adaptation #network #recognition- Rejection strategy for Convolutional Neural Network by adaptive topology applied to handwritten digits recognition (HC, AB), pp. 765–769.
ICDAR-2005-LucasC #grid #performance- Fast Convolutional OCR with the Scanning N-Tuple Grid (SML, KTC), pp. 799–805.
DATE-v2-2004-ZhouZLLZC #analysis #using- Steady-State Analysis of Nonlinear Circuits Using Discrete Singular Convolution Method (XZ, DZ, JL, RL, XZ, CC), pp. 1322–1326.
ICPR-v2-2004-FlusserZ #invariant #symmetry- Invariants to Convolution with Circularly Symmetric PSF (JF, BZ), pp. 11–14.
OOPSLA-2004-ZhangJ04a #middleware- Resolving feature convolution in middleware systems (CZ, HAJ), pp. 188–205.
ICDAR-2003-SimardSP #analysis #documentation #network #visual notation- Best Practices for Convolutional Neural Networks Applied to Visual Document Analysis (PYS, DS, JCP), pp. 958–962.
ICPR-v2-2002-Fasel #analysis #network #robust #using- Robust Face Analysis using Convolutional Neural Networks (BF), pp. 40–43.
ICPR-v3-2000-JohanssonKG #detection #normalisation #symmetry #using- Detecting Rotational Symmetries Using Normalized Convolution (BJ, HK, GHG), pp. 3500–3504.
DATE-1999-Sheehan #reduction #using- Projective Convolution: RLC Model-Order Reduction Using the Impulse Response (BNS), p. 669–?.
ICDAR-1999-TangSMRTC #2d #algorithm #composition- Accelerating the 2-D Mallat Decomposition Algorithm with Cyclical Convolution and FNTT (YYT, QS, HM, DBR, YT, ZKC), pp. 87–90.
PLDI-1991-BromleyHMS #compilation #fortran- Fortran at Ten Gigaflops: The Connection Machine Convolution Compiler (MB, SH, TSM, GLSJ), pp. 145–156.