Description: 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.
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EAN: 9780128034675
UPC: 9780128034675
ISBN: 9780128034675
MPN: N/A
Book Title: Probabilistic Graphical Models for Computer Vision
Item Length: 23.5 cm
Number of Pages: 294 Pages
Publication Name: Probabilistic Graphical Models for Computer Vision.
Language: English
Publisher: Elsevier Science Publishing Co Inc
Item Height: 235 mm
Subject: Engineering & Technology
Publication Year: 2019
Type: Textbook
Item Weight: 770 g
Author: Qiang Ji
Item Width: 191 mm
Format: Hardcover
