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portada Low-Rank and Sparse Modeling for Visual Analysis
Type
Physical Book
Publisher
Author
Language
English
Pages
236
Format
Paperback
Dimensions
23.4 x 15.6 x 1.3 cm
Weight
0.35 kg.
ISBN13
9783319355672

Low-Rank and Sparse Modeling for Visual Analysis

Fu, Yun (Author) · Springer · Paperback

Low-Rank and Sparse Modeling for Visual Analysis - Fu, Yun

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Synopsis "Low-Rank and Sparse Modeling for Visual Analysis"

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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All books in our catalog are Original.
The book is written in English.
The binding of this edition is Paperback.

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