Low-Rank and Sparse Modeling for Visual Analysis

Nonfiction, Computers, Application Software, Computer Graphics, Science & Nature, Technology, Electronics, General Computing
Cover of the book Low-Rank and Sparse Modeling for Visual Analysis by , Springer International Publishing
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Author: ISBN: 9783319120003
Publisher: Springer International Publishing Publication: October 30, 2014
Imprint: Springer Language: English
Author:
ISBN: 9783319120003
Publisher: Springer International Publishing
Publication: October 30, 2014
Imprint: Springer
Language: English

This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data. The book includes chapters covering multiple emerging topics in this new field. It links multiple popular research fields in Human-Centered Computing, Social Media, Image Classification, Pattern Recognition, Computer Vision, Big Data, and Human-Computer Interaction. Contains an overview of the low-rank and sparse modeling techniques for visual analysis by examining both theoretical analysis and real-world applications.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding and learning among unconstrained visual data. The book includes chapters covering multiple emerging topics in this new field. It links multiple popular research fields in Human-Centered Computing, Social Media, Image Classification, Pattern Recognition, Computer Vision, Big Data, and Human-Computer Interaction. Contains an overview of the low-rank and sparse modeling techniques for visual analysis by examining both theoretical analysis and real-world applications.

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