default search action
ESANN 1999: Bruges, Belgium
- 7th European Symposium on Artificial Neural Networks, ESANN 1999, Bruges, Belgium, April 21-23, 1999, Proceedings. 1999
Dynamical systems
- Frank Pasemann:
Synchronizing chaotic neuromodules. 1-6 - Emmanuel Daucé, Olivier Moynot, Olivier Pinaud, Manuel Samuelides, Bernard Doyon:
Mean-field equations reveal synchronization in a 2-populations neural network model. 7-12
Self-organization
- Stefan Schünemann, Bernd Michaelis:
A hierarchical self-organizing feature map for analysis of not well separable clusters of different feature density. 13-18 - Eric de Bodt, Marie Cottrell, Michel Verleysen:
Using the Kohonen algorithm for quick initialization of Simple Competitive Learning algorithm. 19-26
Special session: Adaptive computation of data structures
- Marco Gori:
Learning in structured domains. 27-32 - Barbara Hammer:
Approximation capabilities of folding networks. 33-38 - Andreas Küchler:
Tree-recursive computation of gradient information for structures. 39-44 - Christoph Goller:
Learning search-control heuristics for automated deduction systems with folding architecture networks. 45-50 - Fabrizio Costa, Paolo Frasconi, Giovanni Soda:
A topological transformation for hidden recursive modelsarchitecture networks. 51-56 - Mikel L. Forcada, Antonio M. Corbí-Bellot, Marco Gori, Marco Maggini:
Neural learning of approximate simple regular languages. 57-62 - Markus Hagenbuchner, Ah Chung Tsoi:
A benchmark for testing adaptive systems on structured data. 63-68
Methodology
- Peter J. Edwards, Alan F. Murray, Georgios Papadopoulos, A. Robin Wallace, John Barnard:
The application of neural networks to the paper-making industry. 69-74 - Juan Martínez-Cabeza-de-Vaca-Alajarín, Luis-Manuel Tomás-Balibrea:
Marble slabs quality classification system using texture recognition and neural networks methodology. 75-80 - Andrea Corradini, Hans-Joachim Böhme, Horst-Michael Gross:
Visual-based posture recognition using hybrid neural networks. 81-86 - Bart Bakker, Tom Heskes:
Model clustering by deterministic annealing. 87-92
Special session: Remote sensing spectral image analysis
- Erzsébet Merényi:
The challenges in spectral image analysis: an introduction, and review of ANN approaches. 93-98 - Neil Pendock:
A simple associative neural network for producing spatially homogenous spectral abundance interpretations of hyperspectral imagery. 99-104 - Jörg Bruske, Erzsébet Merényi:
Estimating the intrinsic dimensionality of hyperspectral images. 105-110 - Thomas Villmann:
Benefits and limits of the self-organizing map and its variants in the area of satellite remote sensoring processing. 111-116 - Donald MacDonald, Stephen McGlinchey, John Kawala, Colin Fyfe:
Comparison of Kohonen, scale-invariant and GTM self-organising maps for interpretation of spectral data. 117-122
ANN models and learning I
- Terry Windeatt, Reza Ghaderi:
AdaBoost and neural networks. 123-128 - Francesca Acerra, Yves Burnod, Scania de Schonen:
Modeling face recognition learning in early infant development. 129-134 - John Carney, Padraig Cunningham:
The NeuralBAG algorithm: optimizing generalization performance in bagged neural networks. 135-140 - Valentina Colla, Leonardo Maria Reyneri, Mirko Sgarbi:
Neuro-wavelet parametric characterization of hardness profiles. 141-146 - Shin Mizutani, Katsunori Shimohara:
Heterogeneity enhanced order in a chaotic neural network. 147-152 - Christophe Lecerf:
Tackling the stability/plasticity dilemma with double loop dynamic systems. 153-158
Biological models and inspiration
- John A. Bullinaria, Patricia M. Riddell, Simon K. Rushton:
Regularization in oculomotor adaptation. 159-164 - Heiko Neumann, Wolfgang Sepp:
Recurrent V1-V2 interaction for early visual information processing. 165-170 - Katrin Suder, Florentin Wörgötter, Thomas Wennekers:
Neural field description of state-dependent receptive field changes in the visual cortex. 171-176
Special session: Support Vector Machines
- James Tin-Yau Kwok:
Integrating the evidence framework and the support vector machine. 177-182 - Koji Tsuda:
Support vector classifier with asymetric kernel function. 183-188 - Nello Cristianini, Colin Campbell, John Shawe-Taylor:
A multiplicative updating algorithm for training support vector machine. 189-194 - Rodrigo Fernández, Emmanuel Viennet:
Face identification using support vector machines. 195-200 - Arnaud Buhot, Mirta B. Gordon:
Statistical mechanics of support vector machine. 201-206 - Pierre M. L. Drezet, Robert F. Harrison:
An efficient formulation of sparsity controlled support vector regression. 207-212 - Davide Mattera, Francesco Palmieri, Simon Haykin:
Generalized support vector machines. 213-218 - Jason Weston, Chris Watkins:
Support vector machines for multi-class pattern recognition. 219-224 - Massimiliano Pontil, Ryan M. Rifkin, Theodoros Evgeniou:
From regression to classification in support vector machines. 225-230 - Michèle Sebag:
From first order logic to Nd: a data driven reformulation. 231-236 - Christian Wöhler, Ulrich Kressel, Jürgen Schürmann, Joachim K. Anlauf:
Dimensionality reduction by local processing. 237-244 - Thilo-Thomas Frieß, Robert F. Harrison:
A kernel based adaline. 245-250 - David M. J. Tax, Robert P. W. Duin:
Data domain description using support vectors. 251-256 - N. Barabino, M. Pallavicini, Alessandro Petrolini, Massimiliano Pontil, Alessandro Verri:
Support vector machines vs multi-layer perceptrons in particle identification. 257-262
ANN models and learning II
- Hervé Frezza-Buet, Frédéric Alexandre:
Specialization with cortical models: An application to causality learning. 263-268 - Arnaud Ribert, Abdel Ennaji, Yves Lecourtier:
Generalisation capabilities of a distributed neural classifier. 269-274 - Simone G. O. Fiori, Francesco Piazza:
A comparison of three PCA neural techniques. 275-280 - Donald MacDonald, Darryl Charles, Colin Fyfe:
Neural networks which identify composite factors. 281-288 - Kamal R. Al-Rawi, Consuelo Gonzalo, Agueda Arquero:
Supervised Art-II: a new neural network architecture, with quicker learning algorithm, for learning and classifying multivaled input patterns. 289-294
Classification
- Heiko Wersing, Helge J. Ritter:
Feature binding and relaxation labeling with the competitive layer model. 295-300 - Christian Wöhler, Jürgen Schürmann, Joachim K. Anlauf:
Segmentation-free detection of overtaking vehicles with a two-stage time-delay neural network classifier. 301-306 - Roelof K. Brouwer:
An integer recurrent artificial neural network for classifying feature vectors. 307-312 - Lindsay B. Jack, Asoke K. Nandi:
Feature selection for ANNs using genetic algorithms in condition monitoring. 313-318
Special session: Information extraction using unsupervised neural networks
- Colin Fyfe:
Trends in Unsupervised Learning. 319-326 - Arnaud Buhot, Mirta B. Gordon:
Detection of two Gaussian clusters. 327-332 - Francesco Palmieri, Alessandra Budillon, Davide Mattera:
Independent component analysis for mixture densities. 333-338 - Nicolas Donckers, Amaury Lendasse, Vincent Wertz, Michel Verleysen:
Extraction of intrinsic dimension using CCA - Application to blind sources separation. 339-344 - Darryl Charles, Colin Fyfe:
Noise to extract independent causes. 345-350 - Jan van den Berg, Martijn J. Schuemie:
Information retrieval systems using an associative conceptual space. 351-356 - Arnaud Revel, Philippe Gaussier, Jean-Paul Banquet:
Taking inspiration from the Hippocampus can help solving robotics problems. 357-362
ANN models and learning III
- Valentina Colla, Leonardo Maria Reyneri, Mirko Sgarbi:
Orthogonal least square algorithm applied to the initialization of multi-layer perceptrons. 363-369 - Jochen J. Steil, Helge J. Ritter:
Maximisation of stability ranges for recurrent neural networks subject to on-line adaptation. 370-374 - Ramón P. Ñeco, Mikel L. Forcada, Rafael C. Carrasco, M. Ángeles Valdés-Muñoz:
Encoding of sequential translators in discrete-time recurrent neural nets. 375-380 - Antoine Fache, Olivier Dubois, Alain Billat:
On the invertibility of the RBF model in a predictive control strategy. 381-386 - Anton M. Sirota, Alexander A. Frolov, Dusan Húsek:
Nonlinear factorization in sparsely encoded Hopfield-like neural networks. 387-392 - Bruno Crespi, Ignazio Lazzizzera:
Storage capacity and dynamics of nonmonotonic networks. 393-398 - Fabien Belloir, Antoine Fache, Alain Billat:
A general approach to construct RBF net-based classifier. 399-404 - Stefan Liehr, Klaus Pawelzik, Jens Kohlmorgen, Steven Lemm, Klaus-Robert Müller:
Hidden Markov gating for prediction of change points in switching dynamical systems. 405-410 - Christian W. Eurich, Thorsten Conradi, Helmut Schwegler:
Critical and non-critical avalanche behavior in networks of integrate-and-fire neurons. 411-416
Special session: Spiking neurons
- Thomas Natschläger, Wolfgang Maass:
Fast analog computation in networks of spiking neurons using unreliable synapses. 417-422 - Philipp Häfliger:
Learning a temporal code. 423-428 - Michael Schmitt:
VC dimension bounds for networks of spiking neurons. 429-434 - Stefan D. Wilke, Christian W. Eurich:
What does a neuron talk about? 435-440
Temporal series
- Jean-Marc Boite, Christophe Ris:
Development of a French speech recognizer using a hybrid HMM/MLP system. 441-446 - Yves Moreau, Ellen Lerouge, Herman Verrelst, Joos Vandewalle, Christof Störmann, Peter Burge:
A hybrid system for fraud detection in mobile communications. 447-454 - Joseph Rynkiewicz:
Hybrid HMM/MLP models for times series prediction. 455-462
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2024-12-19 22:01 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: