Multiple Classifier Systems

Name: Multiple Classifier Systems
Brand: Josef Kittler, Fabio Roli
SKU: 616913202
Price: 45.18 EUR
Availability: InStock

Second International Workshop, MCS 2001 Cambridge, UK, July 2-4, 2001 Proceedings

von Josef Kittler, Fabio Roli Verlag: Springer Berlin,

2001 - Erschienen 2001.

Gepflegter, sauberer Zustand. Aus der Auflösung einer renommierten Bibliothek. Kann Stempel beinhalten. 616913/202

Image ANalysis, Algorithmic Learning, Remote Sensing, Classifier SYstems, Classification, Pattern Recognition, Time Series Analysis, Neural Networks, algorithm analysis and problem complexity, Bagging, Multiple Classifier Systems, Boosting, Machine Learning, Document Analysis,

Produktart:: 📚 Bücher
Autor(en):: Kittler, Josef und Fabio Roli:
Anbieter:: Buchpark GmbH
Bestell-Nr.:: 616913202
Katalog:: Varia
ISBN | EAN:: 3540422846 | 9783540422846
Stichworte:: Image, ANalysis, Algorithmic, Learning, Remote, Sensing, Classifier, SYstems, Classification, Pattern, Recognition, Time, Series, Analysis, Neural, Networks, algorithm, analysis, problem, complexity, Bagging, Multiple, Systems, Boosting, Machine, Document…
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Verlagstext

Driven by the requirements of a large number of practical and commercially - portant applications, the last decade has witnessed considerable advances in p- tern recognition. Better understanding of the design issues and new paradigms, such as the Support Vector Machine, have contributed to the development of - proved methods of pattern classi cation. However, while any performance gains are welcome, and often extremely signi cant from the practical point of view, it is increasingly more challenging to reach the point of perfection as de ned by the theoretical optimality of decision making in a given decision framework. The asymptoticity of gains that can be made for a single classi er is a re?- tion of the fact that any particular design, regardless of how good it is, simply provides just one estimate of the optimal decision rule. This observation has motivated the recent interest in Multiple Classi er Systems , which aim to make use of several designs jointly to obtain a better estimate of the optimal decision boundary and thus improve the system performance. This volume contains the proceedings of the international workshop on Multiple Classi er Systems held at Robinson College, Cambridge, United Kingdom (July 2{4, 2001), which was organized to provide a forum for researchers in this subject area to exchange views and report their latest results.