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SpringerBriefs in Computer Science

Robust Recognition via Information Theoretic Learning

Authors: He, R., Hu, B., Yuan, X., Wang, L.

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  • ISBN 978-3-319-07416-0
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About this book

This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy.

The authors resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency, the brief introduces the additive and multiplicative forms of half-quadratic optimization to efficiently minimize entropy problems and a two-stage sparse presentation framework for large scale recognition problems. It also describes the strengths and deficiencies of different robust measures in solving robust recognition problems.

Table of contents (6 chapters)

Table of contents (6 chapters)

Buy this book

eBook $54.99
price for USA in USD
  • ISBN 978-3-319-07416-0
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $69.99
price for USA in USD
  • ISBN 978-3-319-07415-3
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
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Bibliographic Information

Bibliographic Information
Book Title
Robust Recognition via Information Theoretic Learning
Authors
Series Title
SpringerBriefs in Computer Science
Copyright
2014
Publisher
Springer International Publishing
Copyright Holder
The Author(s)
eBook ISBN
978-3-319-07416-0
DOI
10.1007/978-3-319-07416-0
Softcover ISBN
978-3-319-07415-3
Series ISSN
2191-5768
Edition Number
1
Number of Pages
XI, 110
Number of Illustrations
4 b/w illustrations, 25 illustrations in colour
Topics