Multiple Classifier Systems

8th International Workshop, MCS 2009, Reykjavik, Iceland, June 10-12, 2009. Proceedings

  • Jón Atli Benediktsson
  • Josef Kittler
  • Fabio Roli
Conference proceedings MCS 2009
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5519)

Table of contents

  1. Front Matter
  2. ECOC, Boosting and Bagging

    1. Sergio Escalera, Oriol Pujol, Petia Radeva
      Pages 11-21
    2. Satoshi Shirai, Mineichi Kudo, Atsuyoshi Nakamura
      Pages 22-31
    3. Goo Jun, Joydeep Ghosh
      Pages 32-41
  3. MCS in Remote Sensing

    1. Xavier Ceamanos, Björn Waske, Jón Atli Benediktsson, Jocelyn Chanussot, Johannes R. Sveinsson
      Pages 62-71
  4. Unbalanced Data and Decision Templates

    1. David M. J. Tax, Marco Loog, Robert P. W. Duin
      Pages 72-81
    2. Muhammad Atif Tahir, Josef Kittler, Krystian Mikolajczyk, Fei Yan
      Pages 82-91
    3. Mohamed Farouk Abdel Hady, Friedhelm Schwenker
      Pages 92-101
  5. Stacked Generalization and Active Learning

    1. Sam Reid, Greg Grudic
      Pages 112-121
    2. Battista Biggio, Giorgio Fumera, Fabio Roli
      Pages 132-141
  6. Concept Drift, Missing Values and Random Forest

    1. Ryan Elwell, Robi Polikar
      Pages 142-151
    2. Luca Didaci, Gian Luca Marcialis, Fabio Roli
      Pages 152-160
    3. David Windridge, Norman Poh, Vadim Mottl, Alexander Tatarchuk, Andrey Eliseyev
      Pages 161-170
    4. Simon Bernard, Laurent Heutte, Sébastien Adam
      Pages 171-180
  7. SVM Ensembles

    1. Albert D. Shieh, David F. Kamm
      Pages 181-190

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 8th International Workshop on Multiple Classifier Systems, MCS 2009, held in Reykjavik, Iceland, in June 2009.

The 52 revised full papers presented together with 2 invited papers were carefully reviewed and selected from more than 70 initial submissions. The papers are organized in topical sections on ECOC boosting and bagging, MCS in remote sensing, unbalanced data and decision templates, stacked generalization and active learning, concept drift, missing values and random forest, SVM ensembles, fusion of graphics, concepts and categorical data, clustering, and finally theory, methods and applications of MCS.

Keywords

Support Vector Machine algorithmic learning algorithms bayesian networks biometric authentication classification classifier systems data fragmentation decision trees diversity document analysis ensemble learning ensemble prediction image analysis pattern recognition

Editors and affiliations

  • Jón Atli Benediktsson
    • 1
  • Josef Kittler
    • 2
  • Fabio Roli
    • 3
  1. 1.Faculty of Electrical and Computer EngineeringUniversity of IcelandReykjavikIceland
  2. 2.Speech and Signal Processing, GuildfordUniversity of Surrey, Centre for VisionSurreyUnited Kingdom
  3. 3.Department of Electrical and Electronic Engineering, Piazza d’ArmiUniversity of CagliariCagliariItaly

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-02326-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-02325-5
  • Online ISBN 978-3-642-02326-2
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349