Information Theory in Computer Vision and Pattern Recognition

Author: Francisco Escolano Ruiz
Edition: 2009
Publisher: Springer
Binding: Hardcover
ISBN: 1848822960
Category: Programming
List Price: $ 129.00
Price: $ 101.11
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Information Theory in Computer Vision and Pattern Recognition

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). Programming books Information Theory in Computer Vision and Pattern Recognition pdf. 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. Download books Information Theory In Computer Vision And Pattern Recognition pdf via mediafire, 4shared, rapidshare.

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Information Theory in Computer Vision and Pattern Recognition SPRIV 9781848822962 09781848822962

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Springer 9781848822962 Information Theory in Computer Vision and Pattern Recognition Description 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

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author boyan bonev author francisco escolano author pablo suau format hardback language english publication year 31 07 2009 subject computing it subject 2 computing professional programming title information theory in computer vision and pattern recognition author escolano francisco suau pablo bonev boyan yuille alan foreward by publisher springer publication date sep 01 2009 pages 394 binding hardcover edition 1 st dimensions 6 25 wx 9 75 hx 1 00 d isbn 1848822960 subject computers computer v

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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 incremen

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Download Information Theory in Computer Vision and Pattern Recognition

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. Download free Information Theory in Computer Vision and Pattern Recognition pdf