Robust Computer Vision - Computational Imaging and Vision - Nicu Sebe - Books - Springer - 9789048162901 - December 6, 2010
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Robust Computer Vision - Computational Imaging and Vision Softcover Reprint of the Original 1st Ed. 2003 edition

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From the foreword by Thomas Huang:
"During the past decade, researchers in computer vision have found that probabilistic machine learning methods are extremely powerful. This book describes some of these methods. In addition to the Maximum Likelihood framework, Bayesian Networks, and Hidden Markov models are also used. Three aspects are stressed: features, similarity metric, and models. Many interesting and important new results, based on research by the authors and their collaborators, are presented.

Although this book contains many new results, it is written in a style that suits both experts and novices in computer vision."


215 pages, biography

Media Books     Paperback Book   (Book with soft cover and glued back)
Released December 6, 2010
ISBN13 9789048162901
Publishers Springer
Pages 215
Dimensions 170 × 244 × 12 mm   ·   331 g
Language English  

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