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This book offers a systematic introduction to an
understanding-oriented approach to multimedia content analysis. It
integrates the visual understanding and learning models into a
unified framework, within which the visual understanding guides the
model learning while the learned models improve the visual
understanding. More specifically, it discusses multimedia content
representations and analysis including feature selection, feature
extraction, image tagging, user-oriented tag recommendation and
understanding-oriented multimedia applications. The book was
nominated by the University of Chinese Academy of Sciences and
China Computer Federation as an outstanding PhD thesis. By
providing the fundamental technologies and state-of-the-art
methods, it is a valuable resource for graduate students and
researchers working in the field computer vision and machine
learning.
This book offers a systematic introduction to an
understanding-oriented approach to multimedia content analysis. It
integrates the visual understanding and learning models into a
unified framework, within which the visual understanding guides the
model learning while the learned models improve the visual
understanding. More specifically, it discusses multimedia content
representations and analysis including feature selection, feature
extraction, image tagging, user-oriented tag recommendation and
understanding-oriented multimedia applications. The book was
nominated by the University of Chinese Academy of Sciences and
China Computer Federation as an outstanding PhD thesis. By
providing the fundamental technologies and state-of-the-art
methods, it is a valuable resource for graduate students and
researchers working in the field computer vision and machine
learning.
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