14.5.9.5 Neural Networks for Shapes and Complex Features

Gandikota, K.V.[Kanchana Vaishnavi], Geiping, J.[Jonas], Lähner, Z.[Zorah], Czaplinski, A.[Adam], Möller, M.[Michael],
A Simple Strategy to Provable Invariance via Orbit Mapping,
ACCV22(V:387-405).
Springer DOI 2307
Invariance of networkto data transformations. Rotation and scaling. BibRef

Saltori, C.[Cristiano], Roy, S.[Subhankar], Sebe, N.[Nicu], Iacca, G.[Giovanni],
Regularized Evolutionary Algorithm for Dynamic Neural Topology Search,
CIAP19(I:219-230).
Springer DOI 1909
BibRef

Chang, Y., Wu, X., Zhang, S.,
Piecewise Linear Units for Fast Self-Normalizing Neural Networks,
ICPR18(429-434)
IEEE DOI 1812
Biological neural networks, Random variables, Jacobian matrices, Force, Neurons, Pattern recognition, Piecewise linear units, self-normalizing property BibRef

Fan, L.,
Deep Epitome for Unravelling Generalized Hamming Network,
ICPR18(409-416)
IEEE DOI 1812
approximation theory, convolution, data visualisation, neural nets, optimisation, deep epitomes, Feature extraction BibRef

Wang, X.L.[Xiao-Long], Girshick, R.[Ross], Gupta, A.[Abhinav], He, K.M.[Kai-Ming],
Non-local Neural Networks,
CVPR18(7794-7803)
IEEE DOI 1812
Computational modeling, Neural networks, Convolution, Feedforward systems, Convolutional codes BibRef

Meng, Z.H.[Zi-Hang], Adluru, N.[Nagesh], Kim, H.W.J.[Hyun-Woo J.], Fung, G.[Glenn], Singh, V.[Vikas],
Efficient Relative Attribute Learning Using Graph Neural Networks,
ECCV18(XIV: 575-590).
Springer DOI 1810
BibRef

Haeusser, P., Mordvintsev, A., Cremers, D.,
Learning by Association: A Versatile Semi-Supervised Training Method for Neural Networks,
CVPR17(626-635)
IEEE DOI 1711
Data models, Dogs, Neural networks, Training, Training, data BibRef

Knöbelreiter, P., Reinbacher, C., Shekhovtsov, A., Pock, T.,
End-to-End Training of Hybrid CNN-CRF Models for Stereo,
CVPR17(1456-1465)
IEEE DOI 1711
Computational modeling, Correlation, Feature extraction, Neural networks, Robustness, Support vector machines, Training BibRef

Jiang, Z., Wang, Y., Davis, L., Andrews, W., Rozgic, V.,
Learning Discriminative Features via Label Consistent Neural Network,
WACV17(207-216)
IEEE DOI 1609
Biological neural networks, Convergence, Feature extraction, Linear programming, Neurons, Training, Videos BibRef

Hafiz, A.R., Al-Marzouqi, H.,
Efficient neural network training using curvelet features,
IVMSP16(1-5)
IEEE DOI 1608
Biological neural networks BibRef

Movshovitz-Attias, Y.[Yair], Yu, Q.[Qian], Stumpe, M.C.[Martin C.], Shet, V.[Vinay], Arnoud, S.[Sacha], Yatziv, L.[Liron],
Ontological supervision for fine grained classification of Street View storefronts,
CVPR15(1693-1702)
IEEE DOI 1510
BibRef

Kim, E.[Edward], Hannan, D.[Darryl], Kenyon, G.T.[Garrett T.],
Deep Sparse Coding for Invariant Multimodal Halle Berry Neurons,
CVPR18(1111-1120)
IEEE DOI 1812
Neurons, Encoding, Brain modeling, Biological system modeling, Biological neural networks, Visualization, Standards BibRef

Schultz, P.F.[Peter F.], Bettencourt, L.M.[Luis M.], Kenyon, G.T.[Garrett T.],
A symmetry-breaking generative model of a simple-cell/complex-cell hierarchy,
Southwest12(89-92).
IEEE DOI 1205
3 layer neural net BibRef

Hörnlein, T.[Thomas], Jähne, B.[Bernd],
Boosting Shift-Invariant Features,
DAGM09(121-130).
Springer DOI 0909
local convolutions followed by subsampling, then learning. BibRef

Szilágyi, S.M.[Sándor M.], Szilágyi, L.[László], Frigy, A.[Attila], Görög, L.K.[Levente K.], Benyó, Z.[Zoltán],
Unified Neural Network Based Pathologic Event Reconstruction Using Spatial Heart Model,
CIARP07(851-860).
Springer DOI 0711
BibRef

Wersing, H.[Heiko], Kirstein, S.[Stephan], Schneiders, B.[Bernd], Bauer-Wersing, U.[Ute], Körner, E.[Edgar],
Online Learning for Bootstrapping of Object Recognition and Localization in a Biologically Motivated Architecture,
CVS08(xx-yy).
Springer DOI 0805
BibRef

Kirstein, S.[Stephan], Wersing, H.[Heiko], Körner, E.[Edgar],
Rapid Online Learning of Objects in a Biologically Motivated Recognition Architecture,
DAGM05(301).
Springer DOI 0509
BibRef

Doulamis, N.D., Doulamis, A.D.,
Non-linear 3D rendering workload prediction based on a combined fuzzy-neural network architecture for grid computing applications,
ICIP03(III: 1069-1072).
IEEE DOI 0312
BibRef

Loh, A.W.K., Robey, M.C., West, G.A.W.,
IFOSART: a noise resistant neural network capable of incremental learning,
ICPR00(Vol II: 985-988).
IEEE DOI 0403
BibRef

Loh, A.W.K., Robey, M.C., West, G.A.W.,
Refining 3d models using a two-stage neural network-based iterative process,
ICPR02(I: 172-175).
IEEE DOI 0211
BibRef

Villela, P.R.[Patricia Rayon], Sossa Azuela, J.H.[J. Humberto],
Object Recognition by Indexing Using Neural Networks,
ICPR00(Vol II: 1001-1004).
IEEE DOI 0009
BibRef

Papamarkos, N.[Nikos],
Using Local Features in a Neural Network Based Gray-level Reduction Technique,
ICPR00(Vol III: 1025-1028).
IEEE DOI BibRef 0001 ICPR00(Vol III: 1037-1040).
IEEE DOI 0009
BibRef

Webb, A.R., Shannon, S.,
Adaptive Radial Basis Functions,
ICPR96(IV: 630-634).
IEEE DOI 9608
(Defence Res. Agency, UK) BibRef

Webb, A.R.,
Nonlinear Feature Extraction with Radial Basis Functions Using a Weighted Multidimensional Scaling Stress Measure,
ICPR96(IV: 635-639).
IEEE DOI 9608
(Defence Res. Agency, UK) BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Vision Transformers, ViT .

Last update:Sep 28, 2024 at 17:47:54