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Multiple Classifier Systems

11th International Workshop, MCS 2013, Nanjing, China, May 15-17, 2013. Proceedings

  • Conference proceedings
  • © 2013

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Editors:
  1. Zhi-Hua Zhou

    1. National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China

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  2. Fabio Roli

    1. Dept. of Electrical and Electronic Engineering, University of Cagliari, Piazza d’Armi, Cagliari, Italy

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  3. Josef Kittler

    1. Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, UK

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 7872)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

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Conference proceedings info: MCS 2013.

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About this book

This book constitutes the refereed proceedings of the 11th International Workshop on Multiple Classifier Systems, MCS 2013, held in Nanjing, China, in May 2013. The 34 revised papers presented together with two invited papers were carefully reviewed and selected from 59 submissions. The papers address issues in multiple classifier systems and ensemble methods, including pattern recognition, machine learning, neural network, data mining and statistics.

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Table of contents (34 papers)

  1. Front Matter

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  2. Improving Simple Collaborative Filtering Models Using Ensemble Methods

    • Ariel Bar, Lior Rokach, Guy Shani, Bracha Shapira, Alon Schclar
    Pages 1-12

  3. Combining Instance Information to Classify Bags

    • Veronika Cheplygina, David M. J. Tax, Marco Loog
    Pages 13-24

  4. Similarity Weighted Ensembles for Relocating Models of Rare Events

    • Claire D’Este, Ashfaqur Rahman
    Pages 25-36

  5. Diversity in Classifier Ensembles: Fertile Concept or Dead End?

    • Luca Didaci, Giorgio Fumera, Fabio Roli
    Pages 37-48

  6. Gender Classification Using Mixture of Experts from Low Resolution Facial Images

    • Yomna Safaa El-Din, Mohamed N. Moustafa, Hani Mahdi
    Pages 49-60

  7. Multi-view Multi-class Classification for Identification of Pathogenic Bacterial Strains

    • Evgeni Tsivtsivadze, Tom Heskes, Armand Paauw
    Pages 61-72

  8. Feature Level Multiple Model Fusion Using Multilinear Subspace Analysis with Incomplete Training Set and Its Application to Face Image Analysis

    • Zhen-Hua Feng, Josef Kittler, William Christmas, Xiao-Jun Wu
    Pages 73-84

  9. Kalman Filter Based Classifier Fusion for Affective State Recognition

    • Michael Glodek, Stephan Reuter, Martin Schels, Klaus Dietmayer, Friedhelm Schwenker
    Pages 85-94

  10. Adaptive Ensemble Selection for Face Re-identification under Class Imbalance

    • Paulo Radtke, Eric Granger, Robert Sabourin, Dmitry Gorodnichy
    Pages 95-108

  11. Self-Organizing Neural Grove and Its Application to Incremental Learning

    • Hirotaka Inoue
    Pages 109-120

  12. Cascaded Reduction and Growing of Result Sets for Combining Object Detectors

    • Uwe Knauer, Udo Seiffert
    Pages 121-133

  13. Single Classifier Based Multiple Classifications

    • Albert Hung-Ren Ko, Robert Sabourin
    Pages 134-145

  14. Selective Ensemble of Classifier Chains

    • Nan Li, Zhi-Hua Zhou
    Pages 146-156

  15. The Link between Multiple-Instance Learning and Learning from Only Positive and Unlabelled Examples

    • Yan Li, David M. J. Tax, Robert P. W. Duin, Marco Loog
    Pages 157-166

  16. Stable L2-Regularized Ensemble Feature Weighting

    • Yun Li, Shasha Huang, Songcan Chen, Jennie Si
    Pages 167-178

  17. Selective Clustering Ensemble Based on Covariance

    • Xuyao Lu, Yan Yang, Hongjun Wang
    Pages 179-189

  18. Semi-supervised Clustering Ensemble for Web Video Categorization

    • Amjad Mahmood, Tianrui Li, Yan Yang, Hongjun Wang, Mehtab Afzal
    Pages 190-200

  19. Coding Theory Tools for Improving Recognition Performance in ECOC Systems

    • Claudio Marrocco, Paolo Simeone, Francesco Tortorella
    Pages 201-211

  20. Can Diversity amongst Learners Improve Online Object Tracking?

    • Georg Nebehay, Walter Chibamu, Peter R. Lewis, Arjun Chandra, Roman Pflugfelder, Xin Yao
    Pages 212-223
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Other volumes

  1. Multiple Classifier Systems

Editors and Affiliations

  • National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China

    Zhi-Hua Zhou

  • Dept. of Electrical and Electronic Engineering, University of Cagliari, Piazza d’Armi, Cagliari, Italy

    Fabio Roli

  • Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, UK

    Josef Kittler

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