14.5.10 Neural Networks

Chapter Contents (Back)
Neural Networks.
See also Adversarial Networks, Adversarial Inputs, Generative Adversarial.
See also Recurrent Neural Networks for Shapes and Complex Features, RNN.

14.5.10.1 Neural Networks: General, Survey, Special Issues

Chapter Contents (Back)
Survey, Neural Networks. Neural Networks.

van Veen, F.[Fjodor],
A mostly complete chart of Neural Networks,
Online
WWW Link. 2002
The Online link goes to Andrew Tch with explaination of each. The main reference is to the creator of the chart. BibRef

Deep Learning Tool Kit for Medical Imaging,
2017.
WWW Link. Code, Neural Networks. Neural networks toolkit written in python, on top of Tensorflow. Its modular architecture was developed to enable fast prototyping and ensure reproducibility in image analysis applications, with a particular focus on medical imaging.

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Bertin, E., Bischof, H., Bertolino, P.,
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Wang, L.F.[Li-Feng], Cheng, H.D.,
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Willshaw, D., Hallam, J., Gingell, S., Lau, S.L.,
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Abdel-Wahhab, O.[Osama], Sid-Ahmed, M.A.,
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Frasconi, P., Gori, M., Soda, G.,
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Hoekstra, A., Duin, R.P.W.,
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PRL(18), No. 11-13, November 1997, pp. 1293-1300. 9806
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de Ridder, D., Duin, R.P.W.,
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Yan, H., Gupta, M.M.,
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Wilson, C.L., Blue, J.L., Omidvar, O.M.,
Neurodynamics of Learning and Network Performance,
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Wang, S.D., Hsu, T.C.,
Perceptron-Perceptron Net,
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de Ridder, D., Duin, R.P.W., Verbeek, P.W., van Vliet, L.J.,
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Kraaijveld, M.A., Duin, R.P.W.,
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Schmidt, W.F., Kraaijveld, M.A., Duin, R.P.W.,
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Foody, G.M.[Giles M.],
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Asari, K.V.[K. Vijayan], Eswaran, C.,
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Wang, B.Y.[Bao-Yun], He, Z.Y.[Zhen-Ya],
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Hungenahally, S., and Bhattacharya, P.,
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Micheli-Tzanakou, E.[Evangelia],
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Chandra Kumar, P., Saratchandran, P., Sundararajan, N.,
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Zhang, G.P.,
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SMC-C(30), No. 4, November 2000, pp. 451-462.
IEEE Top Reference. 0104
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Murino, V., Vernazza, G.,
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IVC(19), No. 9-10, August 2001, pp. 583-584.
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Raudys, S.J.[Sarunas J.],
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Springer-VerlagNew York, 2001. ISBN 1-85233-297-2. BibRef 0100

Egmont-Petersen, M., de Ridder, D., Handels, H.,
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Ripley, B.D.,
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Ripley, B.D.,
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Behnke, S.,
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Sussner, P.[Peter], Graña, M.[Manuel],
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Foresti, G.L., Dolso, T.,
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Foresti, G.L., Christian, M., Snidaro, L.,
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Lucas, A., Iliadis, M., Molina, R., Katsaggelos, A.K.,
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Convolutional neural network, Deep learning BibRef

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Edwards, C.[Chris],
Deep Learning Hunts for Signals Among the Noise,
CACM(61), No. 6, June 2018, pp. 13-14.
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Neural networks, Critical initialisation, Signal propagation, Randomised control trial BibRef

Lin, R.[Ruiyuan], You, S.[Suya], Rao, R.[Raghuveer], Kuo, C.C.J.[C.C. Jay],
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Neurons, Multilayer perceptrons, Tools, Piecewise linear approximation, Biological neural networks, piecewise polynomial approximation BibRef

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Höfer, T.[Timon], Zell, A.[Andreas],
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Seeing Implicit Neural Representations as Fourier Series,
WACV22(2283-2292)
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ICCV19(2931-2940)
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ICPR21(7544-7550)
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IVCNZ17(1-7)
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Cahill-Lane, J., Mills, S.,
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IVCNZ17(1-6)
IEEE DOI 1902
medical image processing, neural nets, mice, men, artificial deep networks, artificial neural networks, Optical sensors BibRef

Jacob, B., Kligys, S., Chen, B., Zhu, M., Tang, M., Howard, A., Adam, H., Kalenichenko, D.,
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CVPR18(2704-2713)
IEEE DOI 1812
Quantization (signal), Training, Arrays, Computational modeling, Hardware, Neural networks BibRef

Park, E.[Eunhyeok], Yoo, S.[Sungjoo], Vajda, P.[Peter],
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ECCV18(II: 608-624).
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Banerjee, S.[Samik], Bhattacharjee, P.[Prateep], Das, S.[Sukhendu],
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Handa, A.[Ankur], Bloesch, M.[Michael], Patraucean, V.[Viorica], Stent, S.[Simon], McCormac, J.[John], Davison, A.[Andrew],
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Nguyen, A.[Anh], Clune, J.[Jeff], Bengio, Y.[Yoshua], Dosovitskiy, A.[Alexey], Yosinski, J.[Jason],
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CVPR17(3510-3520)
IEEE DOI 1711
Feature extraction, Generators, Image resolution, Neurons, Plugs, Probabilistic logic, Training BibRef

Nguyen, A.[Anh], Yosinski, J.[Jason], Clune, J.[Jeff],
Deep neural networks are easily fooled: High confidence predictions for unrecognizable images,
CVPR15(427-436)
IEEE DOI 1510
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Ben Othman, I.[Ibtissem], Ghorbel, F.[Faouzi],
Stability evaluation of neural and Bayesian classifiers: A new insight,
ICIP14(4314-4317)
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Wu, F.[Fuke], Hu, S.G.[Shi-Geng],
Robust stability with general decay rate for stochastic neural networks with unbounded time-varying delays,
ICARCV12(753-758).
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Karan, S., Majumder, D.D.,
Cognitive Quantum Number: The Logic for Nano Scale Information Processing in Minds and Machines,
NCVPRIPG11(183-186).
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Madani, K.[Kurosh],
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Besdok, E.[Erkan],
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Springer DOI 0706
BibRef

Giraudo, M.T.[Maria Teresa], Sacerdote, L.[Laura], Sicco, A.[Alessandro],
Ghost Stochastic Resonance for a Neuron with a Pair of Periodic Inputs,
BVAI07(398-407).
Springer DOI 0710
BibRef

Zanetti, B., Noriakilde, A., Saito, J.H.,
A Framework for Neural Networks Simulation and Visualization: Neocognitron Case,
ICIP05(III: 485-488).
IEEE DOI 0512
BibRef

Banarer, V.[Vladimir], Perwass, C.[Christian], Sommer, G.[Gerald],
Design of a Multilayered Feed-Forward Neural Network Using Hypersphere Neurons,
CAIP03(571-578).
Springer DOI 0311
BibRef

Silvestre, M.R., Ling, L.L.[Lee Luan],
Optimization of neural classifiers based on Bayesian decision boundaries and idle neurons pruning,
ICPR02(III: 387-390).
IEEE DOI 0211
BibRef

Li, Y.L.[Yan-Lai], Wang, K.Q.[Kuan-Quan], Zhang, D.,
Step acceleration based training algorithm for feedforward neural networks,
ICPR02(II: 84-87).
IEEE DOI 0211
BibRef

Toh, K.A.[Kar-Ann], Mao, K.Z.,
A global transformation approach to RBF neural network learning,
ICPR02(II: 96-99).
IEEE DOI 0211
BibRef

Grim, J., Pudil, P., Somol, P.,
Boosting in probabilistic neural networks,
ICPR02(II: 136-139).
IEEE DOI 0211
BibRef

Cardot, H., Lezoray, O.,
Graph of neural networks for pattern recognition,
ICPR02(II: 873-876).
IEEE DOI 0211
BibRef

Feiden, D., Tetzlaff, R.,
Iterative Annealing: a New Efficient Optimization Method for Cellular Neural Networks,
ICIP01(I: 549-552).
IEEE DOI 0108
BibRef

di Bona, S., Salvetti, O.,
An Efficient Method to Map a Regular Mesh Into a 3d Neural Network,
ICIP01(I: 529-532).
IEEE DOI 0108
BibRef

Wang, G.Y.[Guo-Yin],
Triple- or Multiple-Valued Logical Rule Generation from Neural Network,
ICPR98(ATP1). 9808
BibRef

Eigenmann, R., Nossek, J.A.,
Modification of Hard-Limiting Multilayer Neural Networks for Confidence Evaluation,
ICDAR97(1087-1091).
IEEE DOI 9708
BibRef
Earlier:
Constructive and Robust Combination of Perceptrons,
ICPR96(IV: 195-199).
IEEE DOI 9608
(Technical Univ. of Munich, D) BibRef

Utschick, W., Nossek, J.A.,
Bayesian Adaptation of Hidden Layers in Boolean Feedforward Neural Networks,
ICPR96(IV: 229-233).
IEEE DOI 9608
(Technical Univ. of Munich, D) BibRef

Lampinen, J.[Jouko], and Selonen, A.[Arto],
Using Background Knowledge in Multilayer Perceptron Learning,
SCIA97(xx-yy)
HTML Version. 9705
BibRef

Sardo, L., Kittler, J.V.[Josef V.],
Model Complexity Validation for PDF Estimation Using Gaussian Mixtures,
ICPR98(Vol I: 195-197).
IEEE DOI 9808
BibRef
Earlier:
Minimum Complexity PDF Estimation for Correlated Data,
ICPR96(II: 750-754).
IEEE DOI 9608
BibRef
And:
Complexity analysis of RBF networks for Pattern Recognition,
CVPR96(574-579).
IEEE DOI (Univ. of Surrey, UK) BibRef

Paik, J.H.[Jong-Hyun], Cho, S.B.[Sung-Bae], Lee, K.Y.[Kwan-Yong], Lee, Y.B.[Yill-Byung],
Multiple Recognizers System Using Two Stage Combinations,
ICPR96(IV: 581-585).
IEEE DOI 9608
(Yonsei Univ., KOR) BibRef

Ritter, G., Sussner, P.,
An Introduction to Morphological Neural Networks,
ICPR96(IV: 709-717).
IEEE DOI 9608
(Univ. of Florida, USA) BibRef

Kuncheva, L.I.[Ludmila I.], Hadjitodorov, S.,
An RBF Network with Tunable Function Shape,
ICPR96(IV: 645-649).
IEEE DOI 9608
(Imperial College of Science, UK) BibRef

Bayro-Corrochano, E., Buchholz, S., Sommer, G.,
A New Self-Organizing Neural Network Using Geometric Algebra,
ICPR96(IV: 555-559).
IEEE DOI 9608
(Christian Albrechts Univ., D) BibRef

Stoyanov, I.,
An Improved Backpropagation Neural Network Learning,
ICPR96(IV: 586-588).
IEEE DOI 9608
(Bulgarian Academy of Sciences, BG) BibRef

Wang, S., Zhu, X., Jin, Y.,
Multiple Experts Recognition System Based on Neural Network,
ICPR96(IV: 452-456).
IEEE DOI 9608
(Tshinghua Univ., PRC) BibRef

Vriesenga, M., Sklansky, J.,
Neural Modeling of Piecewise Linear Classifiers,
ICPR96(IV: 281-285).
IEEE DOI 9608
(Univ. of California, Irvine, USA) BibRef

Hamamoto, Y., Mitani, Y., Ishihara, H., Hase, T., Tomita, S.,
Evaluation of an Anti-Regularization Technique in Neural Networks,
ICPR96(IV: 205-208).
IEEE DOI 9608
(Yamaguchi Univ., J) BibRef

Chen, C.H., Jozwik, A.,
On the Small-Sample Behavior of the Class-Sensitive Neural Network,
ICPR96(IV: 209-213).
IEEE DOI 9608
(Univ. of Massachusetts, USA) BibRef

Bachelder, I.A.[Ivan A.], Gove, A.N.[Alan N.], Seibert, M.C.[Michael C.], and Waxman, A.M.[Allen M.],
From Learning Objects to Learning Environments: Biological and Computational Neural Systems,
ARPA94(II:871-883). BibRef 9400

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


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