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Robust Computer Vision Theory and Applications PDF

244 Pages·2010·5.322 MB·English
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by N. Sebe, M.S. Lew| 2010| 244 pages| 5.322| English

About Robust Computer Vision Theory and Applications

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."

Detailed Information

Author:N. Sebe, M.S. Lew
Publication Year:2010
ISBN:9048162904
Pages:244
Language:English
File Size:5.322
Format:PDF
Price:FREE
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