Books > Computing & IT > Applications of computing > Image processing
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Information Theory in Computer Vision and Pattern Recognition (Paperback, 2009 ed.)
Loot Price: R2,815
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Information Theory in Computer Vision and Pattern Recognition (Paperback, 2009 ed.)
Expected to ship within 10 - 15 working days
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Information theory has proved to be effective for solving many
computer vision and pattern recognition (CVPR) problems (such as
image matching, clustering and segmentation, saliency detection,
feature selection, optimal classifier design and many others).
Nowadays, researchers are widely bringing information theory
elements to the CVPR arena. Among these elements there are measures
(entropy, mutual information...), principles (maximum entropy,
minimax entropy...) and theories (rate distortion theory, method of
types...). This book explores and introduces the latter elements
through an incremental complexity approach at the same time where
CVPR problems are formulated and the most representative algorithms
are presented. Interesting connections between information theory
principles when applied to different problems are highlighted,
seeking a comprehensive research roadmap. The result is a novel
tool both for CVPR and machine learning researchers, and
contributes to a cross-fertilization of both areas.
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