14.5.5 Neural Networks

14.5.5.1 Neural Networks: General, Survey, Special Issues

Minsky, M.L.[Marvin L.], Papert, S.,
Perceptrons: An Introduction to Computational Geometry,
MIT PressCambridge, MA, 1969. Whey they do not work. BibRef 6900

Dewdney, A.K.,
Computer Recreations,
SciAmer(250), Month missing -- 1984, pp. 22-34. Perceptrons. Discussion of Perceptrons. BibRef 8400

Pao, Y.H.,
Neural Net Computing for Pattern Recognition,
HPRCV97(Chapter I:4). (Case Western Reserve Univ.) BibRef 9700

Haykin, S.,
Neural Networks: A Comprehensive Introduction,
Prentice Hall1999. BibRef 9900

Skrzypek, J., Karplus, W., (Eds.)
Special Issue-Neural Networks in Vision and Pattern Recognition,
PRAI(6), No. 1, April 1992, pp. 1-208. BibRef 9204

Bischof, H.[Horst], Pinz, A.[Axel],
Artificial Versus Real Neural Networks,
BBS(15), No. 4, 1992, pp. 712. BibRef 9200

Guyun, I., Wang, P.S.P., (Eds.)
Special Issue on Advances in Pattern Recognition Using Neural Networks,
PRAI(8), No. 4, August 1993, pp. 645-963. BibRef 9308

Drucker, H., Schapire, R., Simard, P.Y.,
Boosting Performance in Neural Networks,
PRAI(7), 1993, pp. 705-719. BibRef 9300

Musavi, M.T., Chan, K.H., Hummels, D.M., Kalantri, K.,
On The Generalization Ability Of Neural Network Classifiers,
PAMI(16), No. 6, June 1994, pp. 659-663.
IEEE Abstract. IEEE Top Reference.
WWW Version. BibRef 9406

Marshall, J.A.,
Adaptive Perceptual Pattern-Recognition by Self-Organizing Neural Networks: Context, Uncertainty, Multiplicity, and Scale,
NeurNet(8), No. 3, 1995, pp. 335-362. BibRef 9500

Sethi, I.K.,
Special Section on Artificial Neural Networks for Machine Vision,
MVA(8), No. 5, 1995, pp. 261-261.
HTML Version. BibRef 9500

Wang, S.S., Lin, W.G.,
A New Self-Organizing Neural Model for Invariant Pattern-Recognition,
PR(29), No. 4, April 1996, pp. 677-687.
WWW Version. BibRef 9604

Heikkonen, J., Bulsari, A.,
Special Issue on Neural Networks for Computer Vision Applications,
PRL(17), No. 4, April 4 1996, pp. 317-318. 9605 BibRef

Simes, E.D., Uebel, L.F., Augusto, D., Barone, C.,
Hardware Implementation of RAM Neural Networks,
PRL(17), No. 4, April 4 1996, pp. 421-429. 9605 BibRef

Bertin, E., Bischof, H., Bertolino, P.,
Voronoi Pyramids Controlled by Hopfield Neural Networks,
CVIU(63), No. 3, May 1996, pp. 462-475. 9606
WWW Version. BibRef
Earlier: A2, A1, A3:
Voronoi pyramids and Hopfield networks,
ICPR94(C:330-333).
WWW Version. 9410 BibRef

Sethi, I.K., Yoo, J.H.,
Symbolic Mapping of Neurons in Feedforward Networks,
PRL(17), No. 10, September 2 1996, pp. 1035-1046. Connectionist. BibRef 9609

Chellappa, R., Fukushima, K., Katsaggelos, B.K., Kung, S.Y., Le Cun, Y.L., Nasrabadi, N.M., Poggio, T.A.,
Applications of Artificial Neural Networks to Image Processing,
IP(7), No. 8, August 1998, pp. 1093-1096.
WWW Version. 9808 BibRef

Benediktsson, J.A., Sveinsson, J.R., Ersoy, O.K., Swain, P.H.,
Parallel Consensual Neural Networks,
TNN(8), No. 1, January 1997, pp. 54-64. 9701 BibRef

Mazza, C.,
Neural-Net Inference and Content-Addressable Memory,
TNN(8), No. 1, January 1997, pp. 133-140. 9701 BibRef

Atkinson, P.M., Tatnall, A.R.L.,
Neural Networks in Remote Sensing: Introduction,
JRS(18), No. 4, March 10 1997, pp. 699-709. 9703 BibRef

Wang, L.F., Cheng, H.D.,
Discretizing Continuous Neural Networks Using a Polarization Learning Rule,
PR(30), No. 2, February 1997, pp. 253-260.
WWW Version. 9704 BibRef

Willshaw, D., Hallam, J., Gingell, S., Lau, S.L.,
Marr Theory of the Neocortex as a Self-Organizing Neural-Network,
NeurComp(9), No. 4, May 15 1997, pp. 911-936. 9706 BibRef

Abdelwahhab, O., Sid-Ahmed, M.A.,
A New Scheme for Training Feedforward Neural Networks,
PR(30), No. 3, March 1997, pp. 519-524.
WWW Version. 9705 BibRef

Pandya, A.S.[Abhijit S.], Macy, R.B.[Robert B.],
Pattern Recognition with Neural Networks in C++,
CRC PressBoca Raton, FL. 1996. Code, Neural Networks. ISBN 0-8493-9462-7. Complete code for the various algorithms. BibRef 9600

Frasconi, P., Gori, M., Soda, G.,
Links Between LVQ and Backpropagation,
PRL(18), No. 4, April 1997, pp. 303-310. 9708 BibRef

Hoekstra, A., Duin, R.P.W.,
Investigating Redundancy in Feedforward Neural Classifiers,
PRL(18), No. 11-13, November 1997, pp. 1293-1300. 9806 BibRef

de Ridder, D., Duin, R.P.W.,
Sammons Mapping Using Neural Networks: A Comparison,
PRL(18), No. 11-13, November 1997, pp. 1307-1316. 9806 See also nonlinear mapping for data structure analysis, A. BibRef

Yan, H., Gupta, M.M.,
Special Section on Neural Networks and Fuzzy Logic for Imaging Applications,
JEI(6), No. 3, July 1997, pp. 270-271. 9807 BibRef

Wilson, C.L., Blue, J.L., Omidvar, O.M.,
Neurodynamics of Learning and Network Performance,
JEI(6), No. 3, July 1997, pp. 379-385. 9807 BibRef

Wang, S.D., Hsu, T.C.,
Perceptron-Perceptron Net,
PRL(19), No. 7, May 1998, pp. 559-568. 9808 BibRef

Verikas, A.[Antanas], Lipnickas, A.[Arunas], Malmqvist, K.[Kerstin], Bacauskiene, M.[Marija], Gelzinis, A.[Adas],
Soft combination of neural classifiers: A comparative study,
PRL(20), No. 4, April 1999, pp. 429-444. BibRef 9904

Signahl, M.[Mikael], and Verikas, A.[Antanas],
Fuzzy Combination Schemes for Neural Networks,
SCIA97(xx-yy) 9705
HTML Version. BibRef

Verikas, A., Bacauskiene, M.,
Feature selection with neural networks,
PRL(23), No. 11, September 2002, pp. 1323-1335.
HTML Version. 0206 BibRef

Bacauskiene, M., Verikas, A.,
Selecting salient features for classification based on neural network committees,
PRL(25), No. 16, December 2004, pp. 1879-1891.
WWW Version. 0411 BibRef

de Ridder, D., Duin, R.P.W., Verbeek, P.W., van Vliet, L.J.,
The Applicability of Neural Networks to Non-linear Image Processing,
PAA(2), No. 2, 1999, pp. 111-128. BibRef 9900

de Ridder, D., Duin, R.P.W., Verbeek, P.W., van Vliet, L.J.,
A Weight Set Decorrelating Algorithm for Neural Network Interpretation and Symmetry Breaking,
SCIA99(Neural Nets). BibRef 9900

Duin, R.P.W.[Robert P. W.], de Ridder, D.[Dick],
Neural network experiences between perceptrons and support vectors,
BMVC97(xx-yy).
HTML Version. 0209 BibRef

Kraaijveld, M.A., Duin, R.P.W.,
The effective capacity of multilayer feedforward network classifiers,
ICPR94(B:99-103).
WWW Version. 9410 BibRef

Schmidt, W.F., Kraaijveld, M.A., Duin, R.P.W.,
Feedforward neural networks with random weights,
ICPR92(II:1-4).
WWW Version. 9208 BibRef

Foody, G.M.[Giles M.],
The significance of border training patterns in classification by a feedforward neural network using back propagation learning,
JRS(20), No. 18, December 1999, pp. 3549. BibRef 9912

Varoglu, E., Hacioglu, K.,
Recurrent neural network speech predictor based on dynamical systems approach,
VISP(147), No. 2, April 2000, pp. 149. 0005 BibRef

Asari, K.V.[K. Vijayan], Eswaran, C.,
Bidirectional multiple-valued neural network for pattern recognition and associative recall,
IJIST(11), No. 2, 2000, pp. 125-129. 0008 BibRef

Wang, B.Y.[Bao-Yun], He, Z.[Zhenya],
Can the classification capability of network be further improved by using quadratic sigmoidal neurons?,
PR(33), No. 8, August 2000, pp. 1395-1399.
WWW Version. 0005 BibRef

Hungenahally, S., and Bhattacharya, P.,
A Computational Approach to the Emulation of Visual Neural Architectures,
KBES(2), No. 3, 1998, pp. 185-193. BibRef 9800

Micheli-Tzanakou, E.[Evangelia],
Supervised and Unsupervised Pattern Recognition: Feature Extraction and Computational Intelligence,
CRC PressJanuary 2000, ISBN 0-8493-2278-2. Review of current work. BibRef 0001

Chandra Kumar, P., Saratchandran, P., Sundararajan, N.,
Minimal radial basis function neural networks for nonlinear channel equalisation,
VISP(147), No. 5, October 2000, pp. 428-435. 0101 BibRef

Li, M.B., Huang, G.B., Saratchandran, P., Sundararajan, N.,
Complex-valued growing and pruning RBF neural networks for communication channel equalisation,
VISP(153), No. 4, August 2006, pp. 411-418.
WWW Version. 0705 BibRef

Zhang, G.P.,
Neural networks for classification: a survey,
SMC-C(30), No. 4, November 2000, pp. 451-462.
IEEE Top Reference. 0104 Survey, Neural Networks. BibRef

Murino, V., Vernazza, G.,
Artificial Neural Networks for Image Analysis and Computer Vision,
IVC(19), No. 9-10, August 2001, pp. 583-584.
WWW Version. 0108Special Issue introduction. BibRef

Raudys, S.J.[Sarunas J.],
Statistical and Neural Classifiers: An Integrated Approach to Design,
Springer-VerlagNew York, 2001. ISBN 1-85233-297-2. BibRef 0100

Egmont-Petersen, M., de Ridder, D., Handels, H.,
Image processing with neural networks: A Review,
PR(35), No. 10, October 2002, pp. 2279-2301.
WWW Version. 0206 BibRef

Ripley, B.,
Pattern Recognition and Neural Networks,
Cambridge University Press1996. BibRef 9600

Behnke, S.,
Hierarchical neural networks for image interpretation,
Springer2003, ISBN 3540407227.
PDF Version. BibRef 0300

Sussner, P.[Peter], Graņa, M.[Manuel],
Guest Editorial: Special Issue on Morphological Neural Networks,
JMIV(19), No. 2, September 2003, pp. 79-80.
WWW Version. 0308 BibRef

Foresti, G.L., Dolso, T.,
An Adaptive High-Order Neural Tree for Pattern Recognition,
SMC-B(34), No. 2, April 2004, pp. 988-996.
IEEE Abstract. IEEE Top Reference. 0404 BibRef

Foresti, G.L., Christian, M., Snidaro, L.,
Adaptive high order neural trees for pattern recognition,
ICPR02(II: 877-880).
WWW Version. 0211 BibRef

Oh, K.S.[Kyoung-Su], Jung, K.C.[Kee-Chul],
GPU implementation of neural networks,
PR(37), No. 6, June 2004, pp. 1311-1314.
WWW Version. 0405Graphics Processing Unit implementation of NN. 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).
WWW Version. 0710 BibRef

Zanetti, B., Noriakilde, A., Saito, J.H.,
A Framework for Neural Networks Simulation and Visualization: Neocognitron Case,
ICIP05(III: 485-488).
WWW Version. 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).
WWW Version. 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).
WWW Version. 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).
WWW Version. 0211 BibRef

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

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

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

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

Guoyin, W.[Wang],
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(We-3C) 9708 BibRef

Eigenmann, R., Nossek, J.A.,
Constructive and Robust Combination of Perceptrons,
ICPR96(IV: 195-199).
WWW Version. 9608(Technical Univ. of Munich, D) BibRef

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

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

Paik, J.[Jonghyun], Cho, S.B.[Sung-Bae], Lee, K.[Kwanyong], Lee, Y.B.[Yill-Byung],
Multiple Recognizers System Using Two Stage Combinations,
ICPR96(IV: 581-585).
WWW Version. 9608(Yonsei Univ., KOR) BibRef

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

Song, H.H., Lee, S.W.,
A New Recurrent Neural Network Architecture for Pattern Recognition,
ICPR96(IV: 718-722).
WWW Version. 9608(Korea Univ., KOR) BibRef

Kuncheva, L.I.[Ludmila I.], Hadjitodorov, S.,
An RBF Network with Tunable Function Shape,
ICPR96(IV: 645-649).
WWW Version. 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).
WWW Version. 9608(Christian Albrechts Univ., D) BibRef

Stoyanov, I.,
An Improved Backpropagation Neural Network Learning,
ICPR96(IV: 586-588).
WWW Version. 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).
WWW Version. 9608(Tshinghua Univ., PRC) BibRef

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

Holmstroem, L., Oja, E., Koistinen, P., Laaksonen, J.T.,
Neural Network and Statistical Perspectives of Classification,
ICPR96(IV: 286-290).
WWW Version. 9608(Helsinki Univ. of Technology, SF) BibRef

Hamamoto, Y., Mitani, Y., Ishihara, H., Hase, T., Tomita, S.,
Evaluation of an Anti-Regularization Technique in Neural Networks,
ICPR96(IV: 205-208).
WWW Version. 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).
WWW Version. 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 .