Robust Computer Vision: Theory and Applications

Robust Computer Vision: Theory and Applications

2003 | 215 Pages | ISBN: 9048162904 | PDF | 7 MB

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."


[Fast Download] Robust Computer Vision: Theory and Applications

Related eBooks:
Birds of the Indian Ocean Islands
Statistics Applied to Clinical Trials
Dynasties: The Rise and Fall of Animal Families
New Frontiers in Artificial Intelligence: Joint JSAI 2005 Workshop Post-Proceedings
Transactions on Computational Systems Biology VI
Advances in Computer Games: 11th International Conference, ACG 2005, Taipei, Taiwan, September 6-9,
The Real Chimpanzee: Sex Strategies in the Forest
Hydrogen Exchange Mass Spectrometry of Proteins: Fundamentals, Methods, and Applications
Biomedicine and Beatitude: An Introduction to Catholic Bioethics
Zoo Animal Welfare
The Routledge Companion to Feminist Philosophy
Field Guide to Coral Reefs of the Caribbean/Florida (Peterson Field Guides)
Copyright Disclaimer:
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.