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Low-Rank and Sparse Modeling for Visual Analysis

Low-Rank and Sparse Modeling for Visual Analysis

2014th edition

Hardback (19 Nov 2014)

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Publisher's Synopsis

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.

Book information

ISBN: 9783319119991
Publisher: Springer International Publishing
Imprint: Springer
Pub date:
Edition: 2014th edition
Language: English
Number of pages: 236
Weight: 5354g
Height: 235mm
Width: 155mm
Spine width: 16mm