Low Rank and Sparse Modeling for Visual Analysis is popular PDF and ePub book, written by Yun Fu in 2014-10-30, it is a fantastic choice for those who relish reading online the Computers genre. Let's immerse ourselves in this engaging Computers book by exploring the summary and details provided below. Remember, Low Rank and Sparse Modeling for Visual Analysis can be Read Online from any device for your convenience.
Low Rank and Sparse Modeling for Visual Analysis Book PDF Summary
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.
Detail Book of Low Rank and Sparse Modeling for Visual Analysis PDF
- Author : Yun Fu
- Release : 30 October 2014
- Publisher : Springer
- ISBN : 9783319120003
- Genre : Computers
- Total Page : 240 pages
- Language : English
- PDF File Size : 18,7 Mb
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