| Multiple Classifier Systems: 7th International Workshop, MCS 2007 Prague, Czech Republic, May 23-25, 2007 Proceedings 2007 Edition Contributor(s): Haindl, Michal (Editor), Kittler, Josef (Editor), Roli, Fabio (Editor) |
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ISBN: 3540724818 ISBN-13: 9783540724810 Publisher: Springer OUR PRICE: $52.24 Product Type: Paperback - Other Formats Published: May 2007 Annotation: This book constitutes the refereed proceedings of the 7th International Workshop on Multiple Classifier Systems, MCS 2007, held in Prague, Czech Republic in May 2007. The 49 revised full papers presented together with 2 invited papers were carefully reviewed and selected from more than 80 initial submissions. The papers are organized in topical sections on kernel-based fusion, applications, boosting, cluster and graph ensembles, feature subspace ensembles, multiple classifier system theory, intramodal and multimodal fusion of biometric experts, majority voting, and ensemble learning. |
| Additional Information |
| BISAC Categories: - Computers | Computer Vision & Pattern Recognition - Computers | Computer Science - Computers | Image Processing |
| Dewey: 004 |
| Series: Lecture Notes in Computer Science |
| Physical Information: 1.23" H x 6.34" W x 9.28" (1.79 lbs) 524 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |