Probabilistic Graphical Models for Computer Vision.

Qiang Ji (Autor)

Buch | Hardcover

294 Seiten

2019
Academic Press Inc (Verlag)
978-0-12-803467-5 (ISBN)

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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.

Qiang Ji is in the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute, New York, USA

1. Introduction2. Probability Calculus3. Directed Probabilistic Graphical Models4. Undirected Probabilistic Graphical Models5. PGM Applications in Computer Vision

Erscheinungsdatum	07.11.2017
Verlagsort	San Diego
Sprache	englisch
Maße	191 x 235 mm
Gewicht	770 g
Themenwelt	Mathematik / Informatik ► Informatik
	Naturwissenschaften ► Physik / Astronomie ► Elektrodynamik
	Technik ► Nachrichtentechnik
ISBN-10	0-12-803467-X / 012803467X
ISBN-13	978-0-12-803467-5 / 9780128034675
Zustand	Neuware