Information Theory in Computer Vision and Pattern Recognition 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

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Francisco Escolano Ruiz 作者

Springer

译者

2009-07-24 出版日期

412 页数

USD 129.00 价格

Hardcover

丛书系列

9781848822962 图书编码

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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.

Information Theory in Computer Vision and Pattern Recognition 在线电子书下载 mobi epub pdf txt 在线电子书下载

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