14.5.10.4 Neural Networks for Classification and Pattern Recognition

Chapter Contents (Back)
Neural Networks. Classification.
See also Neural Networks for Segmentation.
See also Capsule Networks.
See also Recurrent Neural Networks for Shapes and Complex Features, RNN.
See also Knowledge Distillation.

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prototype classifiers learn faster than gradient descent methods. BibRef

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Jun, G.[Goo], Ghosh, J.[Joydeep],
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Ravichandran, A., Yegnanarayana, B.,
Studies on Object Recognition from Degraded Images Using Neural Networks,
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Lin, W.G.[Wen-Gou], Wang, S.S.[Shuenn-Shyang],
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And: A2 only:
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Ridella, S., Rovetta, S., Zunino, R.,
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Osman, H., Fahmy, M.M.,
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Osman, H., Fahmy, M.M.,
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Ray, K.S., Ghoshal, J.,
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Ray, K.S.[Kumar S.],
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Ornes, C., Sklansky, J.,
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Auda, G., Kamel, M.,
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Murino, V.,
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Lu, Z.K., Chi, Z.R., Siu, W.C.,
Length Estimation of Digit Strings Using a Neural Network with Structure Based Features,
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Chen, C.W., Chen, L.L.,
Cellular Neural Network Architecture for Gibbs Random Field Based Image Segmentation,
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Chen, C.W., Chen, L.L., Luo, J.B.,
A Cellular Neural Network for Clustering-Based Adaptive Quantization in Subband Video Compression,
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Aizenberg, I.N.,
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Lin, C.C.[Che-Chern], El-Jaroudi, A.[Amro],
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Zhou, W.,
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Carozza, M.[Menita], Rampone, S.[Salvatore],
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Iyatomi, H.[Hitoshi], Hagiwara, M.[Masafumi],
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Iyatomi, H.[Hitoshi], Hagiwara, M.[Masafumi],
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Elsevier DOI 0409
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Raudys, A.,
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Venkatesh, Y.V., Raja, S.K.[S. Kumar],
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Porter, R.B.[Reid B.], Harvey, N.R.[Neal R.], Perkins, S.[Simon], Theiler, J.[James], Brumby, S.P.[Steven P.], Bloch, J.J.[Jeffrey J.], Gokhale, M.[Maya], Szymanski, J.J.[John J.],
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Park, S.B.[Soo Beom], Lee, J.W.[Jae Won], Kim, S.K.[Sang Kyoon],
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Elsevier DOI 0401
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Han, M.[Min], Xi, J.H.[Jian-Hui],
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Sanz, P.J., Marin, R., Sanchez, J.S.,
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Lim, C.P.[Chee-Peng], Leong, J.H.[Jenn-Hwai], Kuan, M.M.[Mei-Ming],
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Artyomov, E.[Evgeny], Yadid-Pecht, O.[Orly],
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PRL(26), No. 6, 1 May 2005, pp. 843-851.
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Yadid-Pecht, O.[Orly], Gur, M.,
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ICPR94(B:520-521).
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Spratling, M.W.[Michael W.],
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PAMI(27), No. 5, May 2005, pp. 753-761.
IEEE Abstract. 0501
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Qin, A.K., Suganthan, P.N.,
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PR(38), No. 8, August 2005, pp. 1275-1288.
Elsevier DOI 0505
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Chi, H.M.[Hoi-Ming], Ersoy, O.K.,
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Zhang, H., Huang, W., Huang, Z., Zhang, B.,
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SMC-B(35), No. 3, June 2005, pp. 593-606.
IEEE DOI 0508
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Perez, C.A., Gonzalez, G.D., Medina, L.E., Galdames, F.J.,
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Cang, S., Yu, H.,
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Ng, W.W.Y.[Wing W.Y.], Dorado, A.[Andres], Yeung, D.S.[Daniel S.], Pedrycz, W.[Witold], and Izquierdo, E.[Ebroul],
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Elsevier DOI 0611
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Chandramouli, K., Izquierdo, E.,
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GeoRS(45), No. 4, April 2007, pp. 800-809.
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Meher, S.K.[Saroj K.], Uma Shankar, B., Ghosh, A.[Ashish],
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Ou, G.B.[Guo-Bin], Murphey, Y.L.[Yi Lu],
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PR(40), No. 1, January 2007, pp. 4-18.
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Machine learning; Multi-class classification; Neural networks BibRef

Murphey, Y.L.[Yi Lu], Luo, Y.[Yun],
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Shankar, B.U.[B. Uma], Meher, S.K.[Saroj K.], Ghosh, A.[Ashish], Bruzzone, L.[Lorenzo],
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Ponalagusamy, R., Senthilkumar, S.,
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Senthilkumar, S.,
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Yu, D.[Dong], Deng, L.[Li],
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Martínez-Rego, D.[David], Fontenla-Romero, O.[Oscar], Alonso-Betanzos, A.[Amparo],
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Martinez-Rego, D.[David], Castillo, E.[Enrique], Fontenla-Romero, O.[Oscar], Alonso-Betanzos, A.[Amparo],
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Benalcázar, M.E.[Marco E.], Brun, M.[Marcel], Ballarin, V.[Virginia], Passoni, I.[Isabel], Meschino, G.[Gustavo], Pra, L.D.[Lucía Dai],
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Chen, B.[Bo], Polatkan, G.[Gungor], Sapiro, G.[Guillermo], Blei, D.[David], Dunson, D.[David], Carin, L.[Lawrence],
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Analytical models; Bayesian methods; Convolution; deep learning BibRef

Goodfellow, I.J.[Ian J.], Courville, A.[Aaron], Bengio, Y.[Yoshua],
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PAMI(35), No. 8, 2013, pp. 1902-1914.
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Courville, A.[Aaron], Desjardins, G., Bergstra, J., Bengio, Y.[Yoshua],
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PAMI(36), No. 9, September 2014, pp. 1874-1887.
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Li, D., Wang, W., Ismail, F.,
Fuzzy Neural Network Technique for System State Forecasting,
Cyber(43), No. 5, 2013, pp. 1484-1494.
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Seyedhosseini, M.[Mojtaba], Tasdizen, T.[Tolga],
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Seyedhosseini, M.[Mojtaba], Paiva, A.R.C.[Antonio R.C.], Tasdizen, T.[Tolga],
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Chen, C.H.[Ching-Han], Kuo, C.M.[Chia-Ming], Yao, T.K.[Tun-Kai], Hsieh, S.H.[Sheng-Hsien],
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Zuo, Z., Wang, G.,
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Alvar, M.[Manuel], Rodriguez-Calvo, A.[Andrea], Sanchez-Miralles, A.[Alvaro], Arranz, A.[Alvaro],
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Springer DOI 1407
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Charalampous, K.[Konstantinos], Gasteratos, A.[Antonios],
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IVC(32), No. 11, 2014, pp. 916-929.
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Deep learning BibRef

Ramirez-Quintana, J.A.[Juan Alberto], Chacon-Murguia, M.I.[Mario Ignacio],
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PR(48), No. 4, 2015, pp. 1137-1149.
Elsevier DOI 1502
Video analysis BibRef

Luo, W.[Wei], Yang, J.[Jian], Xu, W.[Wei], Fu, T.[Tao],
Locality-Constrained Sparse Auto-Encoder for Image Classification,
SPLetters(22), No. 8, August 2015, pp. 1070-1073.
IEEE DOI 1502
image classification BibRef

Harikumar, R., kumar, B.V.[B. Vinoth],
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IJIST(25), No. 1, 2015, pp. 33-40.
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medical images BibRef

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CVPR22(470-479)
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Gradient Deconfliction-Based Training For Multi-Exit Architectures,
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ICIP20(713-717)
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EDLCV20(2899-2908)
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EDLCV20(2968-2977)
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A Human-Centered Neural Network Model with Discriminative Locality Preserving Canonical Correlation Analysis for Image Classification,
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Visualization, Biology, Correlation, Training, Feature extraction, Neural networks, Transforms, Image classification, neural network, canonical correlation analysis BibRef

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Benchmark testing, Biological neural networks, Feature extraction, Kernel, Task analysis, Visualization, visual saliency BibRef

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Optimistic and pessimistic neural networks for object recognition,
ICIP17(350-354)
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Biological neural networks, Computational modeling, Neurons, Predictive models, Task analysis, Training, Uncertainty, Output Modeling BibRef

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Neural Networks for the Reconstruction and Separation of High Energy Particles in a Preshower Calorimeter,
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Haeffele, B.D., Vidal, R.,
Global Optimality in Neural Network Training,
CVPR17(4390-4398)
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Algorithm design and analysis, Biological neural networks, Loss measurement, Minimization, Neurons, Optimization, Training BibRef

Dong, X., Huang, J., Yang, Y., Yan, S.,
More is Less: A More Complicated Network with Less Inference Complexity,
CVPR17(1895-1903)
IEEE DOI 1711
Acceleration, Collaboration, Computational modeling, Convolution, Kernel, Neural networks, Tensile, stress BibRef

Kaoutar, S., Mohamed, E.,
Multi-criteria optimization of neural networks using multi-objective genetic algorithm,
ISCV17(1-4)
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Pareto optimisation, genetic algorithms, minimisation, multilayer perceptrons, vectors, MLPNN, NSGA II algorithm, Pareto set, absolute weights, architecture objective optimization, BibRef

Srinivas, S., Subramanya, A., Babu, R.V.,
Training Sparse Neural Networks,
ECVW17(455-462)
IEEE DOI 1709
Biological neural networks, Complexity theory, Indexes, Logic gates, Sparse matrices, Training BibRef

Meng, N., So, H.K.H., Lam, E.Y.,
Computational single-cell classification using deep learning on bright-field and phase images,
MVA17(190-193)
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Cui, S.Q.[Shu-Qi], Jiang, H.[Hong], Wang, Z.[Zheng], Shen, C.M.[Chao-Min],
Application of neural network based on SIFT local feature extraction in medical image classification,
ICIVC17(92-97)
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Biological neural networks, Feature extraction, Image classification, Medical diagnostic imaging, Neurons, BP neural network, ROI, SIFT, SVM, slide, the, window BibRef

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ICPR16(2682-2687)
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Artificial neural networks, Complexity theory, Correlation, Electromyography, Indexes, Pattern recognition, Silicon BibRef

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Mutual information-based RBM neural networks,
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Hierarchical learning for large multi-class network classification,
ICPR16(2307-2312)
IEEE DOI 1705
Additives, Computational modeling, Covariance matrices, Linear programming, Matrix decomposition, Optimization, Testing BibRef

Kalra, S., Sriram, A., Rahnamayan, S., Tizhoosh, H.R.,
Learning opposites using neural networks,
ICPR16(1213-1218)
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Approximation algorithms, Convergence, Data mining, Neural networks, Optimization, Training, Training, data BibRef

Roy, A., Todorovic, S., Latecki, L.J.,
Context-regularized learning of fully convolutional networks for scene labeling,
ICPR16(3751-3756)
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Context, Labeling, Layout, Semantics, Standards, Training, Training, data BibRef

Nooka, S.P., Chennupati, S., Veerabhadra, K., Sah, S., Ptucha, R.,
Adaptive hierarchical classification networks,
ICPR16(3578-3583)
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SINN: Shepard Interpolation Neural Networks,
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Building a Regular Decision Boundary with Deep Networks,
CVPR17(1886-1894)
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Deep roto-translation scattering for object classification,
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Ocampo-Vega, R.[Ricardo], Sanchez-Ante, G.[Gildardo], Falcon-Morales, L.E.[Luis E.], Sossa, H.[Humberto],
Automatic Construction of Radial-Basis Function Networks Through an Adaptive Partition Algorithm,
MCPR16(198-207).
Springer DOI 1608
BibRef

Sossa, H.[Humberto], Cortés, G.[Griselda], Guevara, E.[Elizabeth],
New Radial Basis Function Neural Network Architecture for Pattern Classification: First Results,
CIARP14(706-713).
Springer DOI 1411
BibRef

Shashi Kumar, M.S., Vimala, K.S., Avinash, N.,
Face distance estimation from a monocular camera,
ICIP13(3532-3536)
IEEE DOI 1402
Back propagation neural network BibRef

Landassuri-Moreno, V.M.[Víctor Manuel], Bustillo-Hernández, C.L.[Carmen L.],
Single-Step-Ahead and Multi-Step-Ahead Prediction with Evolutionary Artificial Neural Networks,
CIARP13(I:65-72).
Springer DOI 1311
BibRef

Orjuela-Cañón, A.D.[Alvaro D.], Delisle-Rodríguez, D.[Denis], López-Delis, A.[Alberto],
Onset and Peak Pattern Recognition on Photoplethysmographic Signals Using Neural Networks,
CIARP13(I:543-550).
Springer DOI 1311
BibRef

Chien, C.J.[Chiang-Ju], Wang, Y.C.[Ying-Chung],
Observer based adaptive control of nonlinear systems using filtered-FNN design,
ICARCV12(52-57).
IEEE DOI 1304
BibRef
And: A2, A1:
An FNN-Based adaptive iterative learning control for a class of nonlinear discrete-time systems,
ICARCV12(447-451).
IEEE DOI 1304
Fuzzy Neural Network BibRef

Zhuo, W.[Wen], Cao, Z.G.[Zhi-Guo], Qin, Y.M.[Yue-Ming], Yu, Z.H.[Zheng-Hong], Xiao, Y.[Yang],
Image classification using HTM cortical learning algorithms,
ICPR12(2452-2455).
WWW Link. 1302
BibRef

Sossa, H.[Humberto], Garro, B.A.[Beatriz A.], Villegas, J.[Juan], Avilés, C.[Carlos], Olague, G.[Gustavo],
Automatic Design of Artificial Neural Networks and Associative Memories for Pattern Classification and Pattern Restoration,
MCPR12(23-34).
Springer DOI 1208
BibRef

Varvak, M.S.[Mark S.],
Pattern Classification Using Radial Basis Function Neural Networks Enhanced with the Rvachev Function Method,
CIARP11(272-279).
Springer DOI 1111
BibRef

Nussbaum-Thom, M.[Markus], Schweiger, R.[Roland], Palm, G.[Günther],
Training of Sparsely Connected MLPs,
DAGM11(356-365).
Springer DOI 1109
Multi-Layer Perceptrons. BibRef

Vajda, S.[Szilard], Fink, G.A.[Gernot A.],
Strategies for Training Robust Neural Network Based Digit Recognizers on Unbalanced Data Sets,
FHR10(148-153).
IEEE DOI 1011
BibRef
And:
Exploring Pattern Selection Strategies for Fast Neural Network Training,
ICPR10(2913-2916).
IEEE DOI 1008
BibRef

Adhyaru, D.M.[Dipak M.], Kar, I.N., Gopal, M.,
Constrained Control of Weakly Coupled Nonlinear Systems Using Neural Network,
PReMI09(567-572).
Springer DOI 0912
BibRef

Huo, P.[Peng], Shiu, S.C.K.[Simon Chi-Keung], Wang, H.B.[Hai-Bo], Niu, B.[Ben],
Case Indexing Using PSO and ANN in Real Time Strategy Games,
PReMI09(106-115).
Springer DOI 0912
BibRef

Dhumal, A.[Abhishek], Narayanan, R.G.[R. Ganesh], Kumar, G.S.[G. Saravana],
Estimation of Tailor-Welded Blank Parameters for Acceptable Tensile Behaviour Using ANN,
PReMI09(140-145).
Springer DOI 0912
BibRef

Jang, H.H.[Hong-Hoon], Park, A.[Anjin], Jung, K.C.[Kee-Chul],
Neural Network Implementation Using CUDA and OpenMP,
DICTA08(155-161).
IEEE DOI 0812
BibRef

Rubi-Velez, A.[Anna], Gomez-Ramirez, E.[Eduardo], Pazienza, G.E.[Giovanni E.],
Computing the Weights of Polynomial Cellular Neural Networks Using Quadratic Programming,
CIARP09(645-652).
Springer DOI 0911
BibRef

Stasiak, B.[Bartlomiej],
Two-Dimensional Fast Orthogonal Neural Network for Image Recognition,
CIARP09(653-660).
Springer DOI 0911
BibRef

Chen, F.Y.[Fang-Yue], Chen, L.[Lin], Jin, W.F.[Wei-Feng],
Robust Designs of Selected Objects Extraction CNN,
CISP09(1-3).
IEEE DOI 0910
cellular neural/nonlinear network. BibRef

Liu, W.[Wei], Li, W.H.[Wen-Hui],
An Algorithmic Framework to the Optimal Mapping Function by a Radial Basis Function Neural Network,
CISP09(1-4).
IEEE DOI 0910
BibRef

Wang, L.[Lei], Wen, X.B.[Xian-Bin], Jiao, X.[Xu], Zhang, J.G.[Jian-Guang],
Object Recognition Using a Bayesian Network Imitating Human Neocortex,
CISP09(1-5).
IEEE DOI 0910
BibRef

Peerasathein, T., Woo, M.[Myung], Gaborski, R.S.,
Biologically Inspired Object Categorization in Cluttered Scenes,
AIPR07(117-122).
IEEE DOI 0710
I.e. recognize what separately from where. Implement the what is it, not where is it. BibRef

Sporns, O.,
Complex neural networks as future tools in imagery analysis,
AIPR04(67-72).
IEEE DOI 0410
BibRef

Flynn, M., Abarbanel, H., Kenyon, G.T.[Garrett T.],
Neurally-based algorithms for image processing,
AIPR04(79-85).
IEEE DOI 0410
BibRef

Firpi, H.A., Goodman, E.,
Swarmed feature selection,
AIPR04(112-118).
IEEE DOI 0410
BibRef

Firpi, H.A., Goodman, E.D.,
Designing templates for cellular neural networks using particle swarm optimization,
AIPR04(119-123).
IEEE DOI 0410
BibRef

Ebner, M.[Marc],
Engineering of Computer Vision Algorithms Using Evolutionary Algorithms,
ACIVS09(367-378).
Springer DOI 0909
BibRef

Xiao, P.[Ping], Shi, Y.X.[Yue-Xiang], Xie, W.L.[Wen-Lan],
A novel method of mapping semantic gap to classify natural images,
IASP09(166-171).
IEEE DOI 0904
gap between low level processing and high level recognition. Color and texture, then Neural Network to map features. BibRef

Scripps, J.[Jerry], Tan, P.N.[Pang-Ning], Chen, F.L.[Fei-Long], Esfahanian, A.H.[Abdol-Hossein],
A matrix alignment approach for link prediction,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Kiranyaz, S.[Serkan], Ince, T.[Turker], Yildirim, A.[Alper], Gabbouj, M.[Moncef],
Unsupervised design of Artificial Neural Networks via multi-dimensional Particle Swarm Optimization,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Barrón, R.[Ricardo], Sossa, H.[Humberto], Cruz, B.[Benjamín],
A New Algorithm for Training Multi-layered Morphological Networks,
CIARP07(546-555).
Springer DOI 0711
BibRef

García, A.[Antonio], León, C.[Carlos], Monedero, I.[Iñigo], Ropero, J.[Jorge],
A Precise Electrical Disturbance Generator for Neural Network Training with Real Level Output,
CIARP07(534-545).
Springer DOI 0711
BibRef

Canales, F.[Fernando], Chacón, M.[Max],
Modification of the Growing Neural Gas Algorithm for Cluster Analysis,
CIARP07(684-693).
Springer DOI 0711
BibRef

Siebel, N.T.[Nils T.], Krause, J.[Jochen], Sommer, G.[Gerald],
Efficient Learning of Neural Networks with Evolutionary Algorithms,
DAGM07(466-475).
Springer DOI 0709
BibRef

Stanojevic, M.[Mladen], Vraneš, S.[Sanja],
Applying Neural Networks to Knowledge Representation and Determination of Its Meaning,
BVAI07(523-532).
Springer DOI 0710
BibRef

di Garbo, A.[Angelo], Barbi, M.[Michele], Chillemi, S.[Santi],
Coincidence Detector Properties of Small Networks of Interneurons,
BVAI07(408-417).
Springer DOI 0710
BibRef

Domijan, D.[Dražen], Šetic, M.[Mia],
Computing the Maximum Using Presynaptic Inhibition with Glutamate Receptors,
BVAI07(418-427).
Springer DOI 0710
BibRef

Pazienti, A.[Antonio], Diesmann, M.[Markus], Grün, S.[Sonja],
Bounds of the Ability to Destroy Precise Coincidences by Spike Dithering,
BVAI07(428-437).
Springer DOI 0710
BibRef

Oberhoff, D.[Daniel], Kolesnik, M.[Marina],
Neural Object Recognition by Hierarchical Learning and Extraction of Essential Shapes,
BVAI07(288-297).
Springer DOI 0710
BibRef

Kumar, N.[Niraj], Agrawal, A.[Anupam],
Nonparametric Neural Network Model Based on Rough-Fuzzy Membership Function for Classification of Remotely Sensed Images,
ICCVGIP06(106-117).
Springer DOI 0612
BibRef

Nandedkar, A.V., Biswas, P.K.,
Object Recognition Using Reflex Fuzzy Min-Max Neural Network with Floating Neurons,
ICCVGIP06(597-609).
Springer DOI 0612
BibRef
Earlier:
A Reflex Fuzzy Min Max Neural Network for Granular Data Classification,
ICPR06(II: 650-653).
IEEE DOI 0609
BibRef
Earlier:
A fuzzy min-max neural network classifier with compensatory neuron architecture,
ICPR04(IV: 553-556).
IEEE DOI 0409
BibRef

Bianchini, M.[Monica], Maggini, M.[Marco], Sarti, L.[Lorenzo],
Object Localization Using Input/Output Recursive Neural Networks,
ICPR06(III: 95-98).
IEEE DOI 0609
BibRef
And:
Object Recognition Using Multiresolution Trees,
SSPR06(331-339).
Springer DOI 0608
BibRef

Nieuwenhuis, C.[Claudia], Yan, M.[Michelle],
Knowledge Based Image Enhancement Using Neural Networks,
ICPR06(III: 814-817).
IEEE DOI 0609
BibRef

Zhang, Q.A.[Qi-Ang], Liu, W.B.[Wen-Bing], Wei, X.P.[Xiao-Peng], Xu, J.[Jin],
Globally Exponential Stability of Non-autonomous Delayed Neural Networks,
IbPRIA05(II:91).
Springer DOI 0509
BibRef

Wehrmann, F.[Felix], Bengtsson, E.[Ewert],
Modelling Non-linearities in Images Using an Auto-associative Neural Network,
CAIP03(754-761).
Springer DOI 0311
BibRef

Perwass, C.[Christian], Banarer, V.[Vladimir], Sommer, G.[Gerald],
Spherical Decision Surfaces Using Conformal Modelling,
DAGM03(9-16).
Springer DOI 0310
Award, GCPR, HM. Hypersphere neuron. BibRef

Huang, Y.S.[Yea-Shuan], Tsai, Y.H.[Yao-Hong],
An RBF-based pattern recognition method by competitively reducing classification-oriented error,
ICPR02(II: 180-183).
IEEE DOI 0211
BibRef

Toh, K.A.[Kar-Ann], Lu, J.W.[Ju-Wei], Yau, W.Y.[Wei-Yun],
Global Feedforward Neural Network Learning for Classification and Regression,
EMMCVPR01(407-422).
Springer DOI 0205
BibRef

Gentili, S.,
Information Update on Neural Tree Networks,
ICIP01(I: 505-508).
IEEE DOI 0108
BibRef

Raudys, S.J.,
Prior Weights in Adaptive Pattern Classification,
ICPR00(Vol II: 1010-1013).
IEEE DOI 0009
BibRef

Aizenberg, I., Aizenberg, N., Butakov, C., Farberov, E.,
Image Recognition on the Neural Network Based on Multi-valued Neurons,
ICPR00(Vol II: 989-992).
IEEE DOI 0009
Faces. BibRef

Fyfe, C., Lai, P.L.,
Canonical Correlation Analysis Neural Networks,
ICPR00(Vol II: 977-980).
IEEE DOI 0009
BibRef

Messer, K., Kittler, J.V.,
Fast Unit Selection Algorithm for Neural Network Design,
ICPR00(Vol II: 981-984).
IEEE DOI 0009
BibRef

de Sousa, R., de Carvalho, J.M., de Assis, F.,
Designing Translation Invariant Operations Via Neural Network Training,
ICIP00(Vol I: 908-911).
IEEE DOI 0008
BibRef

Heidemann, G., Lücke, D., Ritter, H.,
A System for Various Visual Classification Tasks Based on Neural Networks,
ICPR00(Vol I: 9-12).
IEEE DOI 0009
BibRef

Mingo, L.F.[Luis F.], Arroyo, F.[Fernando], Luengo, C.[Carmen], Castellanos, J.[Juan],
Enhanced Neural Networks and Medical Imaging,
CAIP99(149-156).
Springer DOI 9909
BibRef
And:
Learning HyperSurfaces with Neural Networks,
SCIA99(Neural Nets). BibRef

Jahn, H.[Herbert],
Feature Grouping Based on Graphs and Neural Networks,
CAIP99(568-577).
Springer DOI 9909
BibRef

Shimodaira, H.[Hiroshi], Keeni, K.[Kanad], Nakayama, K.[Kenji],
Automatic Generation of Initial Weights and Estimation of Hidden Units for Pattern Classification Using Neural Networks,
ICPR98(Vol II: 1568-1571).
IEEE DOI 9808
BibRef

Chen, Z.Y., Desai, M.D., and Zhang, X.,
Feedforward Neural Networks with Multilevel Hidden Neurons for Remotely Sensed Image Classification,
ICIP97(II: 653-656).
IEEE DOI BibRef 9700

Gorodnichy, D.O.[Dmitry O.], Reznik, A.M.[Alexandre M.],
Static and dynamic attractors of autoassociative neural networks,
CIAP97(II: 238-245).
Springer DOI 9709
BibRef

Timchenko, L.I.[Leonid I.], Kutaev, Y.F.[Yuri F.], Grudin, M.A.[Maxim A.], Chepornyuk, S.V.[Serge V.], Harvey, D.M.[David M.], Gertsiy, A.A.[Alexander A.],
A brain-like approach to multistage hierarchical image processing,
CIAP97(II: 246-253).
Springer DOI 9709
BibRef

Foltyniewicz, R.[Rafal],
Efficient high order neural network for rotation, translation and distance invariant recognition of gray scale images,
CAIP95(424-431).
Springer DOI 9509
BibRef

Aizenberg, N., Aizenberg, I.N., Krivosheev, G.,
Multi-Valued and Universal Binary Neurons: Mathematical Model, Learning, Networks, Application to Image Processing and Pattern Recognition,
ICPR96(IV: 185-189).
IEEE DOI 9608
(Univ. of Uzhgorod, UKR) BibRef

Michaelis, B., Schnelting, O., Seiffert, U., Mecke, R.,
Adaptive Filtering of Distorted Displacement Vector Fields Using Artificial Neural Networks,
ICPR96(IV: 335-339).
IEEE DOI 9608
(Otto-von-Guericke-Univ., D) BibRef

Michaelis, B.[Bernd], Krell, G.[Gerald],
Artificial neural networks for image improvement,
CAIP93(838-845).
Springer DOI 9309
BibRef

Pereira, M.S., Manolakos, E.S.,
Hierarchical neural network for multiresolution image analysis,
ICIP96(I: 261-264).
IEEE DOI 9610
BibRef

Petkov, N.[Nikolay],
Use of cortical filters and neural networks in a self-organising image classification system,
CIAP95(165-170).
Springer DOI 9509
BibRef

Lin, S.H.[Shang-Hung], Kung, S.Y.,
Probabilistic DBNN via expectation-maximization with multi-sensor classification applications,
ICIP95(III: 236-239).
IEEE DOI 9510
BibRef

Chan, Y., Kung, S.Y.,
Multi-level pixel difference classification methods,
ICIP95(III: 252-255).
IEEE DOI 9510
BibRef

Dunstone, E.S.,
Image processing using an image approximation neural network,
ICIP94(III: 912-916).
IEEE DOI 9411
BibRef

Miyauchi, A., Watanabe, A., Miyauchi, M.,
A method to interpret 3D motion using neural networks,
ICIP94(III: 83-87).
IEEE DOI 9411
BibRef

Biriukov, S.A.,
Spurious states detection and basin describing in feedforward neural networks,
ICPR94(B:586-588).
IEEE DOI 9410
BibRef

Mascarilla, L., Zahzah, E.H., Desachy, J.,
Neural networks classifiers based on geocoded data and multispectral images for satellite image interpretation,
CAIP93(830-837).
Springer DOI 9309
BibRef

Pan, H.P., Forstner, W.,
An MDL-principled evolutionary mechanism to automatic architecturing of pattern recognition neural network,
ICPR92(II:25-28).
IEEE DOI 9208
BibRef

Nedeljkovic, V.,
A novel multilayer neural networks training algorithm that minimizes the probability of classification error,
ICPR92(II:13-16).
IEEE DOI 9208
BibRef

Roy, A.,
On linear programming, neural network design, pattern classification and polynomial time training,
ICPR92(II:5-8).
IEEE DOI 9208
BibRef

Cheng, X.S., Backer, E., Gerbrands, J.J.,
DRBP: dynamically reinforced BP-based ANN-training,
ICPR92(II:9-12).
IEEE DOI 9208
BibRef

Tambouratzis, G.[George], Stonham, T.J.,
A logical neural network that adapts to changes in the pattern environment,
ICPR92(II:46-49).
IEEE DOI 9208
BibRef

Gas, B., Natowicz, R.,
A model of formal neural networks for unsupervised learning of binary temporal sequences,
ICPR92(II:541-544).
IEEE DOI 9208
BibRef

Singer, Y., Yair, E.,
Learning class probabilities from labeled data,
ICPR92(II:553-556).
IEEE DOI 9208
BibRef

Kamata, S.I., Niimi, M., Kawaguchi, E.,
A multi-temporal classification of multi-spectral images using a neural network,
ICPR94(B:470-472).
IEEE DOI 9410
BibRef

Kamata, S.I., Eason, R.O., Perez, A., Kawaguchi, E.,
A neural network classifier for LANDSAT image data,
ICPR92(II:573-576).
IEEE DOI 9208
BibRef

Kamada, H.[Hiroshi],
A proposal for an artificial neural network that optimizes reference vectors: FMNET,
ICPR92(III:590-593).
IEEE DOI 9208
BibRef

Patrikar, A.,
Dual networks and their pattern classification properties,
CVPR91(686-687).
IEEE DOI 0403
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Capsule Networks .


Last update:Mar 16, 2024 at 20:36:19