Kernel Learning Algorithms for Face Recognition
Autor Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Panen Limba Engleză Hardback – 8 sep 2013
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Specificații
ISBN-13: 9781461401605
ISBN-10: 1461401607
Pagini: 244
Ilustrații: XV, 225 p. 58 illus., 19 illus. in color.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.48 kg
Ediția:2014
Editura: Springer
Colecția Springer
Locul publicării:New York, NY, United States
ISBN-10: 1461401607
Pagini: 244
Ilustrații: XV, 225 p. 58 illus., 19 illus. in color.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.48 kg
Ediția:2014
Editura: Springer
Colecția Springer
Locul publicării:New York, NY, United States
Public țintă
ResearchCuprins
Introduction.- Statistical Learning and Face Recognition.- Kernel Learning Foundation.- Kernel Principal Analysis Based Face Recognition.- Kernel Discriminant Analysis Based Face Recognition.- Kernel Manifold Learning Based Face Recognition.- Kernel Semi-supervised Based Face Recognition.- Kernel Learning Based Face Recognition for Smart Environment.- Kernel Optimization Based Face Recognition.- Kernel Construction for Face Recognition.
Notă biografică
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.
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.
Textul de pe ultima copertă
This book discusses the advanced kernel learning algorithms and its application on face recognition. The book focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. This authors aim to solve the parameter selection problems endured by kernel learning algorithms, and presents kernel optimization method with the data dependent kernel. This text extends the definition of data-dependent kernel and applies it to kernel optimization. Included within are algorithms of kernel based face recognition and the feasibility of the kernel based face recognition method.
Caracteristici
Discusses the system framework of kernel based face recognition Introduces a new method of machine learning as it relates to face recognition Presents algorithms for pattern recognition and machine learning