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Artificial Neural Networks in Pattern Recognition

6th IAPR TC 3 International Workshop, ANNPR 2014, Montreal, QC, Canada, October 6-8, 2014, Proceedings

  • Conference proceedings
  • © 2014

Overview

Editors:
  1. Neamat Gayar

    1. Faculty of Computers and Information, Orman, Cairo University, Giza, Egypt

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  2. Friedhelm Schwenker

    1. Institute for Neural Information Processing, University of Ulm, Ulm, Germany

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  3. Cheng Suen

    1. Department of Computer Science and Software Engineering, Concordia University, Monral, Canada

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 8774)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: ANNPR 2014.

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About this book

This book constitutes the refereed proceedings of the 6th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2014, held in Montreal, QC, Canada, in October 2014. The 24 revised full papers presented were carefully reviewed and selected from 37 submissions for inclusion in this volume. They cover a large range of topics in the field of learning algorithms and architectures and discussing the latest research, results, and ideas in these areas.

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Table of contents (25 papers)

  1. Front Matter

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  2. Invited Paper

    1. Large Margin Distribution Learning

      • Zhi-Hua Zhou
      Pages 1-11

  3. Learning Algorithms and Architectures

    1. A Decorrelation Approach for Pruning of Multilayer Perceptron Networks

      • Hazem M. Abbas
      Pages 12-22

    2. Unsupervised Active Learning of CRF Model for Cross-Lingual Named Entity Recognition

      • Mohamed Farouk Abdel Hady, Abubakrelsedik Karali, Eslam Kamal, Rania Ibrahim
      Pages 23-34

    3. Incremental Feature Selection by Block Addition and Block Deletion Using Least Squares SVRs

      • Shigeo Abe
      Pages 35-46

    4. Low-Dimensional Data Representation in Data Analysis

      • Alexander Bernstein, Alexander Kuleshov
      Pages 47-58

    5. Analyzing Dynamic Ensemble Selection Techniques Using Dissimilarity Analysis

      • Rafael M. O. Cruz, Robert Sabourin, George D. C. Cavalcanti
      Pages 59-70

    6. Hidden Markov Models Based on Generalized Dirichlet Mixtures for Proportional Data Modeling

      • Elise Epaillard, Nizar Bouguila
      Pages 71-82

    7. Majority-Class Aware Support Vector Domain Oversampling for Imbalanced Classification Problems

      • Markus Kächele, Patrick Thiam, Günther Palm, Friedhelm Schwenker
      Pages 83-92

    8. Forward and Backward Forecasting Ensembles for the Estimation of Time Series Missing Data

      • Tawfik A. Moahmed, Neamat El Gayar, Amir F. Atiya
      Pages 93-104

    9. Dynamic Weighted Fusion of Adaptive Classifier Ensembles Based on Changing Data Streams

      • Christophe Pagano, Eric Granger, Robert Sabourin, Gian Luca Marcialis, Fabio Roli
      Pages 105-116

    10. Combining Bipartite Graph Matching and Beam Search for Graph Edit Distance Approximation

      • Kaspar Riesen, Andreas Fischer, Horst Bunke
      Pages 117-128

    11. Computing Upper and Lower Bounds of Graph Edit Distance in Cubic Time

      • Kaspar Riesen, Andreas Fischer, Horst Bunke
      Pages 129-140

    12. Linear Contrast Classifiers in High-Dimensional Spaces

      • Florian Schmid, Ludwig Lausser, Hans A. Kestler
      Pages 141-152

    13. A New Multi-class Fuzzy Support Vector Machine Algorithm

      • Friedhelm Schwenker, Markus Frey, Michael Glodek, Markus Kächele, Sascha Meudt, Martin Schels et al.
      Pages 153-164

    14. A Reinforcement Learning Algorithm to Train a Tetris Playing Agent

      • Patrick Thiam, Viktor Kessler, Friedhelm Schwenker
      Pages 165-170

    15. Bio-Inspired Optic Flow from Event-Based Neuromorphic Sensor Input

      • Stephan Tschechne, Roman Sailer, Heiko Neumann
      Pages 171-182

  4. Applications

    1. Prediction of Insertion-Site Preferences of Transposons Using Support Vector Machines and Artificial Neural Networks

      • Maryam Ayat, Michael Domaratzki
      Pages 183-192

    2. Automatic Bridge Crack Detection – A Texture Analysis-Based Approach

      • Sukalpa Chanda, Guoping Bu, Hong Guan, Jun Jo, Umapada Pal, Yew-Chaye Loo et al.
      Pages 193-203

    3. Part-Based High Accuracy Recognition of Serial Numbers in Bank Notes

      • Bo-Yuan Feng, Mingwu Ren, Xu-Yao Zhang, Ching Y. Suen
      Pages 204-215
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Other volumes

  1. Artificial Neural Networks in Pattern Recognition

Editors and Affiliations

  • Faculty of Computers and Information, Orman, Cairo University, Giza, Egypt

    Neamat Gayar

  • Institute for Neural Information Processing, University of Ulm, Ulm, Germany

    Friedhelm Schwenker

  • Department of Computer Science and Software Engineering, Concordia University, Monral, Canada

    Cheng Suen

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