ESANN 2000:
Bruges,
Belgium
ESANN 2000, 8th European Symposium on Artificial Neural Networks, Bruges, Belgium, April 26-28, 2000, Proceedings.
2000 BibTeX
Data and signal analysis
Support Vector Machines
Model selection and evaluation
Artificial neural networks and robotics
- Richard J. Duro, José Santos Reyes, José Antonio Becerra, Francisco Bellas, José Luis Crespo:
Using higher order synapses and nodes to improve sensing capabilities of mobile robots.
81-88
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- Elsa Fernandez, Imanol Echave, Manuel Graña:
Competitive neural networks for robust computation of the optical flow.
89-94
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- Francesco Panerai, Giorgio Metta, Giulio Sandini:
Learning VOR-like stabilization reflexes in robots.
95-102
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- Roberto Iglesias, Manuel Fernández Delgado, Senén Barro:
Learning of perceptual states in the design of an adaptive wall-following behavior.
103-108
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ANN models and learning I
- Wen-Jyi Hwang, Chien-Min Ou, Shi-Chiang Liao, Ching-Fung Chine:
Fuzzy entropy-constrained competitive learning algorithm.
109-116
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- Gianluigi Rech:
Specification, estimation and evaluation of single hidden-layer feedforward autoregressive artificial neural network models.
117-122
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- Lu Wei, Jagath C. Rajapakse:
A neural network for undercomplete independent component analysis.
123-128
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- Aleksandar Lazarevic, Dragoljub Pokrajac, Zoran Obradovic:
Distributed clustering and local regression for knowledge discovery in multiple spatial databases.
129-134
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- Frank Heister, Gregor Schock:
Nonlinear, statistical data-analysis for the optimal construction of neural-network inputs with the concept of a mutual information.
439-444
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- Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Influence of weight-decay training in input selection methods.
135-140
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- Peter J. Edwards, Alan F. Murray:
Committee formation for reliable and accurate neural prediction in industry.
141-146
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Non-linear dynamics and control
Neural networks in medicine
- Thomas Villmann:
Neural networks approaches in medicine - a review of actual developments.
165-176
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- Tim W. Nattkemper, Heiko Wersing, Walter Schubert, Helge Ritter:
A neural network architecture for automatic segmentation of fluorescence micrographs.
177-182
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- Guojun Bao, Jagath C. Rajapakse:
Boundary based movement correction of functional MR data using a genetic algorithm.
183-188
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- Axel Wismüller, Frank Vietze, Dominik R. Dersch, Klaus Hahn, Helge Ritter:
A neural network approach to adaptive pattern analysis - the deformable feature map.
189-194
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- Armando Bazzani, Alessandro Bevilacqua, Dante Bollini, Rosa Brancaccio, Renato Campanini, Nico Lanconelli, Alessandro Riccardi, Davide Romani, Gianluca Zamboni:
Automatic detection of clustered microcalcifications in digital mammograms using an SVM classifier.
195-200
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- Rüdiger W. Brause, F. Friedrich:
A neuro-fuzzy approach as medical diagnostic interface.
201-206
Electronic Edition (link) BibTeX
ANN models and learning II
- John A. Bullinaria, Patricia M. Riddell:
Regularization in oculomotor control.
207-212
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- Barbara Hammer:
Limitations of hybrid systems.
213-218
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- Elio D. Di Claudio, Raffaele Parisi, Gianni Orlandi:
Discriminative learning for neural decision feedback equalizers.
219-226
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- M. A. Torres, M. E. Pardo, J. M. Pupo, Luciano Boquete, Rafael Barea, Luis Miguel Bergasa:
Neurocontrol of a binary distillation column.
227-232
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- Rafael Barea, Luciano Boquete, Manuel Mazo, Elena López Guillén, Luis Miguel Bergasa:
E.O.G. guidance of a weelchair using spiking neural networks.
233-238
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Self-organizing maps for data analysis
Recurrent networks
Time series prediction
- Johan A. K. Suykens, Joos Vandewalle:
The K.U.Leuven competition data: a challenge for advanced neural network techniques.
299-304
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- James McNames:
Local model optimization for time series prediction.
305-310
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- Gianluca Bontempi, Mauro Birattari:
A multi-steap ahead prediction method based on local dynamic properties.
311-316
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- Ulrich Parlitz, Christian Merkwirth:
Nonlinear prediction of spatio-temporal time series.
317-322
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- Maurits D. Out, Walter A. Kosters:
A Bayesian approach to combined neural networks forecasting.
323-328
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- Amaury Lendasse, John Aldo Lee, Vincent Wertz, Michel Verleysen:
Time series forecasting using CCA and Kohonen maps - application to electricity consumption.
329-334
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- Anna Lombardi, Antonio Vicino:
Financial predictions based on bootstrap-neural networks.
335-340
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- Skander Soltani:
On the use of the wavelet decomposition for time series prediction.
341-346
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- Luis Monzón Benítez, Ademar Ferreira, Diana I. Pedreira Iparraguirre:
Chaotic time series prediction using the Kohonen algorithm.
347-352
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- Patrick Rousset:
Curve forecast with the SOM algorithm: using a tool to follow the time on a Kohonen map.
353-358
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ANN models and learning III
Artificial neural networks for energy management systems
Learning in biological and artificial systems
Copyright © Sat May 16 23:10:41 2009
by Michael Ley (ley@uni-trier.de)
