Authors:
- Researchers in Computer Vision has found, in recent years, that Machine Learning tools are extremely powerful. Thus, all in the CV communication should acquire expertise in ML. Our book is the first and currently only one that presents the most important methods of ML in CV.
- Our book presents not only theories, but also algorithms and applications. Thus, it is useful for practitioners as well as graduate students.
Part of the book series: Computational Imaging and Vision (CIVI, volume 29)
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Table of contents (11 chapters)
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Front Matter
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Back Matter
Reviews
From the foreword by Arnold Smeulders
Authors and Affiliations
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University of Amsterdam, The Netherlands
N. Sebe
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HP Research Labs, USA
Ira Cohen
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Google Inc., USA
Ashutosh Garg
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University of Illinois at Urbana-Champaign, Urbana, USA
Thomas S. Huang
Bibliographic Information
Book Title: Machine Learning in Computer Vision
Authors: N. Sebe, Ira Cohen, Ashutosh Garg, Thomas S. Huang
Series Title: Computational Imaging and Vision
DOI: https://doi.org/10.1007/1-4020-3275-7
Publisher: Springer Dordrecht
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Science+Business Media B.V. 2005
eBook ISBN: 978-1-4020-3275-2Published: 04 October 2005
Series ISSN: 1381-6446
Edition Number: 1
Number of Pages: XVI, 242
Topics: Computer Imaging, Vision, Pattern Recognition and Graphics, User Interfaces and Human Computer Interaction, Multimedia Information Systems, Probability and Statistics in Computer Science