Image Processing, Computer Vision, Pattern Recognition, and Graphics

Multiple Classifier Systems

7th International Workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007, Proceedings

Editors: Haindl, Michal, Kittler, Josef, Roli, Fabio (Eds.)

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About this book

These proceedings are a record of the Multiple Classi?er Systems Workshop, MCS 2007, held at the Institute of Information Theory and Automation, Czech Academy of Sciences, Prague in May 2007. Being the seventh in a well-established series of meetings providing an international forum for the discussion of issues in multiple classi?er system design, the workshop achieved its objective of bringing together researchers from diverse communities (neural networks, pattern rec- nition, machine learning and statistics) concerned with this research topic. From more than 80 submissions, the Programme Committee selected 49 - pers to create an interesting scienti?c programme. The special focus of MCS 2007 was on the application of multiple classi?er systems in biometrics. This part- ular application area exercises all aspects of multiple classi?er fusion, from - tramodal classi?er combination, through con?dence-based fusion, to multimodal biometric systems. The sponsorship of MCS 2007 by the European Union N- work of Excellence in Biometrics BioSecure and in Multimedia Understanding through Semantics, Computation and Learning MUSCLE and their assistance in selecting the contributions to the MCS 2007 programme consistent with this theme is gratefully acknowledged.

Table of contents (51 chapters)

  • Combining Pattern Recognition Modalities at the Sensor Level Via Kernel Fusion

    Mottl, Vadim (et al.)

    Pages 1-12

  • The Neutral Point Method for Kernel-Based Combination of Disjoint Training Data in Multi-modal Pattern Recognition

    Windridge, David (et al.)

    Pages 13-21

  • Kernel Combination Versus Classifier Combination

    Lee, Wan-Jui (et al.)

    Pages 22-31

  • Deriving the Kernel from Training Data

    Merler, Stefano (et al.)

    Pages 32-41

  • On the Application of SVM-Ensembles Based on Adapted Random Subspace Sampling for Automatic Classification of NMR Data

    Lienemann, Kai (et al.)

    Pages 42-51

Buy this book

eBook $109.00
price for USA (gross)
  • ISBN 978-3-540-72523-7
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $139.00
price for USA
  • ISBN 978-3-540-72481-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Multiple Classifier Systems
Book Subtitle
7th International Workshop, MCS 2007, Prague, Czech Republic, May 23-25, 2007, Proceedings
Editors
  • Michal Haindl
  • Josef Kittler
  • Fabio Roli
Series Title
Image Processing, Computer Vision, Pattern Recognition, and Graphics
Series Volume
4472
Copyright
2007
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-540-72523-7
DOI
10.1007/978-3-540-72523-7
Softcover ISBN
978-3-540-72481-0
Edition Number
1
Number of Pages
XI, 524
Topics