Probabilistic Graphical Models for Computer Vision. PDF
By:Qiang Ji
Published on 2019-12-12 by Academic Press
Probabilistic Graphical Models for Computer Vision introduces probabilistic graphical models (PGMs) for computer vision problems and teaches how to develop the PGM model from training data. This book discusses PGMs and their significance in the context of solving computer vision problems, giving the basic concepts, definitions and properties. It also provides a comprehensive introduction to well-established theories for different types of PGMs, including both directed and undirected PGMs, such as Bayesian Networks, Markov Networks and their variants. Discusses PGM theories and techniques with computer vision examples Focuses on well-established PGM theories that are accompanied by corresponding pseudocode for computer vision Includes an extensive list of references, online resources and a list of publicly available and commercial software Covers computer vision tasks, including feature extraction and image segmentation, object and facial recognition, human activity recognition, object tracking and 3D reconstruction
This Book was ranked at 39 by Google Books for keyword computer vision medical robotics.
Book ID of Probabilistic Graphical Models for Computer Vision.'s Books is mN3WDgAAQBAJ, Book which was written byQiang Jihave ETAG "7HTVAHmkNKc"
Book which was published by Academic Press since 2019-12-12 have ISBNs, ISBN 13 Code is 9780128034958 and ISBN 10 Code is 0128034955
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Book which have "294 Pages" is Printed at BOOK under CategoryComputers
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