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Li, Jun-Bao; Chu, Shu-Chuan; Pan, Jeng-Shyang - Kernel Learning Algorithms for Face Recognition - 9781493952120 - V9781493952120
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Kernel Learning Algorithms for Face Recognition

€ 128.75
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Description for Kernel Learning Algorithms for Face Recognition Paperback. This book covers the framework of kernel based face recognition. It discusses the advanced kernel learning algorithms and its application on face recognition. The book also focuses on the theoretical deviation, the system framework and experiments. Num Pages: 240 pages, 39 black & white illustrations, 19 colour illustrations, 69 black & white tables, biograp. BIC Classification: TJK; TTBM; UYQ; UYT. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 13. Weight in Grams: 379.
Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its newest applications.

Product Details

Format
Paperback
Publication date
2016
Publisher
Springer-Verlag New York Inc. United States
Number of pages
240
Condition
New
Number of Pages
225
Place of Publication
New York, United States
ISBN
9781493952120
SKU
V9781493952120
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

About Li, Jun-Bao; Chu, Shu-Chuan; Pan, Jeng-Shyang
Jeng-Shyang Pan is the Tainan Chapter Chair, IEEE Signal Processing Society. Jun-Bao Li is currently at the Department of Automatic Test and Control, Harbin Institute of Technology. Shu-Chuan Chu is a researcher at the School of Electrical and Information Engineering, University of South Australia, Mawson Lakes Campus.

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