Multiple Classifier Systems

12th International Workshop, MCS 2015, Günzburg, Germany, June 29 - July 1, 2015, Proceedings

  • Friedhelm Schwenker
  • Fabio Roli
  • Josef Kittler
Conference proceedings MCS 2015
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9132)

Table of contents

  1. Front Matter
    Pages I-X
  2. Theory and Algorithms

    1. Front Matter
      Pages 1-1
    2. Peter N. Robinson, Marco Frasca, Sebastian Köhler, Marco Notaro, Matteo Re, Giorgio Valentini
      Pages 15-26
    3. Ayako Mikami, Mineichi Kudo, Atsuyoshi Nakamura
      Pages 27-37
    4. Firat Ismailoglu, I. G. Sprinkhuizen-Kuyper, Evgueni Smirnov, Sergio Escalera, Ralf Peeters
      Pages 38-50
    5. Firat Ismailoglu, Evgueni Smirnov, Nikolay Nikolaev, Ralf Peeters
      Pages 51-63
    6. Fábio Pinto, Carlos Soares, João Mendes-Moreira
      Pages 64-75
    7. Nan Li, Yuan Jiang, Zhi-Hua Zhou
      Pages 76-88
    8. Raphael Lattke, Ludwig Lausser, Christoph Müssel, Hans A. Kestler
      Pages 100-111
    9. Nikolaos Nikolaou, Gavin Brown
      Pages 112-124
    10. Kaspar Riesen, Miquel Ferrer, Andreas Fischer
      Pages 125-134
    11. Kaspar Riesen, Miquel Ferrer, Horst Bunke
      Pages 147-156
  3. Application and Evaluation

    1. Front Matter
      Pages 157-157
    2. Hao-Zhi Hong, Jen-Ing G. Hwang
      Pages 159-167
    3. Battista Biggio, Igino Corona, Zhi-Min He, Patrick P. K. Chan, Giorgio Giacinto, Daniel S. Yeung et al.
      Pages 168-180
    4. Juan J. Rodríguez, José F. Díez-Pastor, Álvar Arnaiz-González, César García-Osorio
      Pages 181-193
    5. Mario Barbareschi, Salvatore Del Prete, Francesco Gargiulo, Antonino Mazzeo, Carlo Sansone
      Pages 194-205

About these proceedings

Introduction

This book constitutes the refereed proceedings of the 12th International Workshop on Multiple Classifier Systems, MCS 2015, held in Günzburg, Germany, in June/July 2015. The 19 revised papers presented were carefully reviewed and selected from 25 submissions. The papers address issues in multiple classifier systems and ensemble methods, including pattern recognition, machine learning, neural network, data mining and statistics. They are organized in topical sections on theory and algorithms and application and evaluation.

Keywords

Classification Classifier ensembles Classifier fusion Clustering Cost-sensitive Decision tree Ensemble learning Feature selection Feature weighting Kernel fusion Metalearning Movie genres Multi-class classification Parallel genetic algorithm Pattern recognition Social tags Stability Stepwise search algorithm Variable selection Visual features

Editors and affiliations

  • Friedhelm Schwenker
    • 1
  • Fabio Roli
    • 2
  • Josef Kittler
    • 3
  1. 1.Ulm UniversityUlmGermany
  2. 2.University of CagliariCagliariItaly
  3. 3.University of SurreyGuildfordUnited Kingdom

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-20248-8
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-20247-1
  • Online ISBN 978-3-319-20248-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349