Kernel Learning Algorithms for Face Recognition

Buch | Hardcover
225 Seiten
2013 | 2013
Springer-Verlag New York Inc.
978-1-4614-0160-5 (ISBN)

Lese- und Medienproben

Kernel Learning Algorithms for Face Recognition - Jun-Bao Li, Shu-Chuan Chu, Jeng-Shyang Pan
149,79 inkl. MwSt
Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method.
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.

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.

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.

Zusatzinfo 69 Tables, black and white; 19 Illustrations, color; 39 Illustrations, black and white; XV, 225 p. 58 illus., 19 illus. in color.
Verlagsort New York, NY
Sprache englisch
Maße 155 x 235 mm
Gewicht 4912 g
Themenwelt Informatik Grafik / Design Digitale Bildverarbeitung
Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Technik Elektrotechnik / Energietechnik
Technik Nachrichtentechnik
ISBN-10 1-4614-0160-7 / 1461401607
ISBN-13 978-1-4614-0160-5 / 9781461401605
Zustand Neuware
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