Artificial Neural Networks in Pattern Recognition

Third IAPR Workshop, ANNPR 2008 Paris, France, July 2-4, 2008 Proceedings

  • Editors
  • Lionel Prevost
  • Simone Marinai
  • Friedhelm Schwenker
Conference proceedings ANNPR 2008

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5064)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 5064)

Table of contents

  1. Front Matter
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  2. Unsupervised Learning

    1. Patch Relational Neural Gas – Clustering of Huge Dissimilarity Datasets
      Alexander Hasenfuss, Barbara Hammer, Fabrice Rossi
      Pages 1-12
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    2. The Block Generative Topographic Mapping
      Rodolphe Priam, Mohamed Nadif, Gérard Govaert
      Pages 13-23
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    3. Kernel k-Means Clustering Applied to Vector Space Embeddings of Graphs
      Kaspar Riesen, Horst Bunke
      Pages 24-35
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    4. Probabilistic Models Based on the Π-Sigmoid Distribution
      Anastasios Alivanoglou, Aristidis Likas
      Pages 36-43
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    5. How Robust Is a Probabilistic Neural VLSI System Against Environmental Noise
      C. C. Lu, C. C. Li, H. Chen
      Pages 44-53
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  3. Supervised Learning

    1. Sparse Least Squares Support Vector Machines by Forward Selection Based on Linear Discriminant Analysis
      Shigeo Abe
      Pages 54-65
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    2. Supervised Incremental Learning with the Fuzzy ARTMAP Neural Network
      Jean-François Connolly, Eric Granger, Robert Sabourin
      Pages 66-77
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    3. Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics
      M. Strickert, P. Schneider, J. Keilwagen, T. Villmann, M. Biehl, B. Hammer
      Pages 78-89
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    4. Neural Approximation of Monte Carlo Policy Evaluation Deployed in Connect Four
      Stefan Faußer, Friedhelm Schwenker
      Pages 90-100
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    5. Cyclostationary Neural Networks for Air Pollutant Concentration Prediction
      Monica Bianchini, Ernesto Di Iorio, Marco Maggini, Augusto Pucci
      Pages 101-112
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    6. Fuzzy Evolutionary Probabilistic Neural Networks
      V. L. Georgiou, Ph. D. Alevizos, M. N. Vrahatis
      Pages 113-124
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    7. Experiments with Supervised Fuzzy LVQ
      Christian Thiel, Britta Sonntag, Friedhelm Schwenker
      Pages 125-132
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    8. A Neural Network Approach to Similarity Learning
      Stefano Melacci, Lorenzo Sarti, Marco Maggini, Monica Bianchini
      Pages 133-136
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    9. Partial Discriminative Training of Neural Networks for Classification of Overlapping Classes
      Cheng-Lin Liu
      Pages 137-146
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  4. Multiple Classifiers

    1. Boosting Threshold Classifiers for High– Dimensional Data in Functional Genomics
      Ludwig Lausser, Malte Buchholz, Hans A. Kestler
      Pages 147-156
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    2. Decision Fusion on Boosting Ensembles
      Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo
      Pages 157-167
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    3. The Mixture of Neural Networks as Ensemble Combiner
      Mercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa
      Pages 168-179
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    4. Combining Methods for Dynamic Multiple Classifier Systems
      Amber Tomas
      Pages 180-192
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    5. Researching on Multi-net Systems Based on Stacked Generalization
      Carlos Hernández-Espinosa, Joaquín Torres-Sospedra, Mercedes Fernández-Redondo
      Pages 193-204
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About these proceedings

Keywords

artificial neural networks attribute dependence modeling bayesian classifiers bio-inspired computation bioinformatics biometrics clustering computational intelligence data mining dimensionality reduction dynamic classification face recognition machine learning pattern recognition unsupervised learning

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-69939-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-69938-5
  • Online ISBN 978-3-540-69939-2
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book