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ORCIDESANN 2001: Bruges, Belgium
- 9th European Symposium on Artificial Neural Networks, ESANN 2001, Bruges, Belgium, April 25-27, 2001, Proceedings. 2001
Pattern recognition - classification
- Andreas Alexander Albrecht, Martin J. Loomes, Kathleen Steinhöfel, Matthias Taupitz, Chak-Kuen Wong:
A local search method for pattern classification. 1-6 - Chellu Chandra Sekhar, Kazuya Takeda, Fumitada Itakura:
Recognition of consonant-vowel utterances using Support Vector Machines. 7-12 - Tony Van Gestel, Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
Automatic relevance determination for Least Squares Support Vector Machines classifiers. 13-18
Signal processing and vision
- Axel Wismüller, Oliver Lange, Dominik R. Dersch, Klaus Hahn, Gerda L. Leinsinger:
Analysis of dynamic perfusion MRI data by neural networks. 19-24 - Bogdan Raducanu, Manuel Graña:
Visual self-localization with morphological neural networks. 25-30 - Carlos García Puntonet, Ali Mansour, Manuel Rodríguez Álvarez, Beatriz Prieto, Ignacio Rojas Ruiz:
A stochastic and competitive network for the separation of sources. 31-38 - Vincent Vigneron, Ludovic Aubry:
More on stationnary points in Independent Component Analysis. 39-44
Dedicated hardware implementations: prespectives on systems and applications
- Davide Anguita, Maurizio Valle:
Perspectives on dedicated hardware implementations. 45-56 - Ángel Rodríguez-Vázquez, Servando Espejo-Meana, Rafael Domínguez-Castro, Ricardo Carmona-Galán, Gustavo Liñán:
CMOS design of focal plane programmable array processors. 57-62 - Patrice Fleury, Robin Woodburn, Alan F. Murray:
Matching analogue hardware with applications using the Products of Experts algorithm. 63-68 - Jordi Cosp, Jordi Madrenas:
A microelectronic implementation of a bioinspired analog matrix for object segmentation of a visual scene. 69-74 - Andrea Boni, Fabio Bardi:
Intelligent hardware for identification and control of non-linear systems with SVM. 75-80
Novel neural transfer functions
- Wlodzislaw Duch, Norbert Jankowski:
Transfer functions: hidden possibilities for better neural networks. 81-94 - Pawel Strumillo, Wladyslaw Kaminski:
Neural networks with orthogonalised transfer functions. 95-100 - Norbert Jankowski, Wlodzislaw Duch:
Optimal transfer function neural networks. 101-106 - Wlodzislaw Duch, Rafal Adamczak, Geerd H. F. Diercksen:
Constructive density estimation network based on several different separable transfer functions. 107-112
ANN models and learning I
- Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Coding the outputs of multilayer feedforward. 113-118 - Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Weight initialization methods for multilayer feedforward. 119-124 - Michal Steuer, Praminda Caleb-Solly, Jim E. Smith:
An alternative approach for the evaluation of the neocognitron. 125-130 - Martin Bogdan, Wolfgang Rosenstiel:
Detection of cluster in Self-Organizing Maps for controlling a prostheses using nerve signals. 131-136
Neural networks and evolutionary/genetic algorithms - hybrid approaches
- Thomas Villmann:
Evolutionary algorithms and neural networks in hybrid systems. 137-152 - Paulo Cortez, Miguel Rocha, José Neves:
Lamarckian training of feedforward neural networks. 153-158 - Udo Seiffert:
Multiple Layer Perceptron training using genetic algorithms. 159-164 - Karl-Theodor Kalveram, Ulrich Nakte:
Motor control and movement optimization learned by combining auto-imitative and genetic algorithms. 165-170 - Fernando Fernández, Pedro Isasi:
Designing nearest neighbour classifiers by the evolution of a population of prototypes. 171-178 - Jutta Huhse, Andreas Zell:
Investigating the influence of the neighborhood attraction factor to evolution strategies with neighborhood attraction. 179-184 - I. Chalkiadakis, George A. Rovithakis, Michael E. Zervakis:
A structural genetic algorithm to optimize High Order Neural Network architecture. 185-192 - Domingo Ortiz-Boyer, César Hervás-Martínez, José Muñoz-Pérez:
Genetic algorithms with crossover based on confidence interval as an alternative to traditional nonlinear regression methods. 193-198 - Ignacio Rojas Ruiz, José Luis Bernier, Eduardo Ros Vidal, Fernando J. Rojas, Carlos García Puntonet:
The synergy between multideme genetic algorithms and fuzzy systems. 199-204
ANN models and learning II
- Rudolph van der Merwe, Eric A. Wan:
Efficient derivative-free Kalman filters for online learning. 205-210 - Adam I. Wilmer, Tania Stathaki, Steve R. Gunn, Robert I. Damper:
Texture analysis with the Volterra model using conjugate gradient optimisation. 211-216 - Francesco Diotalevi, Maurizio Valle:
Weight perturbation learning algorithm with local learning rate adaptation for the classification of remote-sensing images. 217-222
Neural networks in finance
- Eric de Bodt, Joseph Rynkiewicz, Marie Cottrell:
Some known facts about financial data. 223-236 - Amaury Lendasse, John Aldo Lee, Eric de Bodt, Vincent Wertz, Michel Verleysen:
Input data reduction for the prediction of financial time series. 237-244 - Vassilis S. Kodogiannis, A. Lolis:
Prediction of foreign exchange rates by neural network and fuzzy system based techniques. 245-250 - Alex Aussem, C. Boutevin:
Segmentation of switching dynamics with a Hidden Markov Model of neural prediction experts. 251-256
Data processing
- Michelangelo Diligenti, Marco Gori, Marco Maggini, Franco Scarselli:
Searching the Web: learning based techniques. 257-264 - Victoria J. Hodge, Jim Austin:
An integrated neural IR system. 265-270 - Thorsten Bojer, Barbara Hammer, Daniel Schunk, Katharina Tluk von Toschanowitz:
Relevance determination in Learning Vector Quantization. 271-276 - Esa Alhoniemi, Olli Simula:
Interpretation and comparison of multivariate data partitions. 277-282 - Barbara Hammer, Thomas Villmann:
Input pruning for neural gas architectures. 283-288
Dynamical systems and chaos
- Brijnesh J. Jain, Fritz Wysotzki:
On the short-term-memory of WTA nets. 289-294 - Nigel T. Crook, Tjeerd Olde Scheper:
A novel chaotic neural network architecture. 295-300
Artificial neural networks and early vision processing
- Darryl Charles, Colin Fyfe:
Unsupervised models for processing visual data. 301-308 - Magnus Borga, Hans Knutsson:
Canonical correlation analysis in early vision processing. 309-314 - Tino Lourens, Kazuhiro Nakadai, Hiroshi G. Okuno, Hiroaki Kitano:
A computational model of monkey grating cells for oriented repetitive alternating patterns. 315-322 - Stefan D. Wilke, Andreas Thiel, Christian W. Eurich, Martin Greschner, Markus Bongard, Josef Ammermüller, Helmut Schwegler:
Extracting motion information using a biologically realistic model retina. 323-328 - Tino Lourens, Kazuhiro Nakadai, Hiroshi G. Okuno, Hiroaki Kitano:
Graph extraction from color images. 329-334 - L. Tan, Colin Fyfe:
Sparse Kernel Canonical Correlation Analysis. 335-340
ANN models and learning III
- Xavier Parra, Andreu Català:
Learning fault-tolerance in Radial Basis Function Networks. 341-346 - César Hervás-Martínez, José Antonio Martinez Heras, Sebastián Ventura, Manuel Silva:
A two steps method: non linear regression and pruning neural network for analyzing multicomponent mixtures. 347-352 - Tarek El. Tobely, Yuichiro Yoshiki, Ryuichi Tsuda, Naoyuki Tsuruta, Makoto Amamiya:
SOM competition for complex image scene with variant object positions. 353-358 - Miguel A. Atencia Ruiz, Gonzalo Joya Caparrós, Francisco Sandoval Hernández:
Numerical implementation of continuous Hopfield networks for optimization. 359-364 - Roelof K. Brouwer, Witold Pedrycz:
One-to-many mappings represented on feed-forward networks. 365-370 - Gerald H. L. Cheang, Andrew R. Barron:
Penalized least squares, model selection, convex hull classes and neural nets. 371-376 - Yoshifusa Ito, Cidambi Srinivasan:
Bayesian decision theory on three layered neural networks. 377-382 - Joseph Rynkiewicz:
Estimation of Hybrid HMM/MLP models. 383-390 - Patrice Wira, Jean-Philippe Urban, Julien Gresser:
A divide-and-conquer learning architecture for predicting unknown motion. 391-396 - Emilio Corchado, Darryl Charles, Colin Fyfe:
Rectified Gaussian distributions and the formation of local filters from video data. 397-402 - Elena Bellei, Diego Guidotti, Ruggero Petacchi, Leonardo Maria Reyneri, Italo Rizzi:
Applications of neuro-fuzzy classification, evaluation and forecasting techniques in agriculture. 403-408
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