Overview
- Describes the latest research trends in compressed sensing, covering sparse representation, modeling and learning
- Examines sensing applications in visual recognition, including sparsity induced similarity, and sparse coding-based classifying frameworks
- Discusses in detail the theory and algorithms of compressed sensing
- Includes supplementary material: sn.pub/extras
Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)
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Table of contents (9 chapters)
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Introduction and Fundamentals
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Sparse Representation, Modeling and Learning
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Visual Recognition Applications
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Advanced Topics
Keywords
About this book
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Sparse Representation, Modeling and Learning in Visual Recognition
Book Subtitle: Theory, Algorithms and Applications
Authors: Hong Cheng
Series Title: Advances in Computer Vision and Pattern Recognition
DOI: https://doi.org/10.1007/978-1-4471-6714-3
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag London 2015
Hardcover ISBN: 978-1-4471-6713-6Published: 09 June 2015
Softcover ISBN: 978-1-4471-7251-2Published: 09 October 2016
eBook ISBN: 978-1-4471-6714-3Published: 25 May 2015
Series ISSN: 2191-6586
Series E-ISSN: 2191-6594
Edition Number: 1
Number of Pages: XIV, 257
Number of Illustrations: 73 b/w illustrations
Topics: Pattern Recognition, Image Processing and Computer Vision, Artificial Intelligence