Modern machine learning techniques and their applications in cartoon animation research /
General Material Designation
[Book]
First Statement of Responsibility
Jun Yu, Dacheng Tao.
EDITION STATEMENT
Edition Statement
First edition
Edition Statement
First edition
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (xii, 196 pages) :
Other Physical Details
illustrations (some color).
SERIES
Series Title
IEEE Press series on systems science and engineering
GENERAL NOTES
Text of Note
"Systems, Man, & Cybernetics Society."
Text of Note
Edition statement from running title area
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references and index
CONTENTS NOTE
Text of Note
Introduction -- Modern machine learning techniques -- Animation research: a brief introduction -- Animation research: modern techniques -- Index
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SUMMARY OR ABSTRACT
Text of Note
The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignment framework; spectral clustering, graph cuts, and convex relaxation; ensemble manifold learning; multiple kernel learning; multiview subspace learning; and multiview distance metric learning. It then presents the applications of these modern machine learning techniques in cartoon animation research. With these techniques, users can efficiently utilize the cartoon materials to generate animations
OTHER EDITION IN ANOTHER MEDIUM
Title
Modern machine learning techniques and their applications in cartoon animation research.