Computer Vision - Statistical Models for Marr's Paradigm (Hardcover, 1st ed. 2023)

As the first book of a three-part series, this book is offered as a tribute to pioneers in vision, such as Bela Julesz, David Marr, King-Sun Fu, Ulf Grenander, and David Mumford. The authors hope to provide foundation and, perhaps more importantly, further inspiration for continued research in vision. This book covers David Marr's paradigm and various underlying statistical models for vision. The mathematical framework herein integrates three regimes of models (low-, mid-, and high-entropy regimes) and provides foundation for research in visual coding, recognition, and cognition. Concepts are first explained for understanding and then supported by findings in psychology and neuroscience, after which they are established by statistical models and associated learning and inference algorithms. A reader will gain a unified, cross-disciplinary view of research in vision and will accrue knowledge spanning from psychology to neuroscience to statistics.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	March 2023
First published:	2023
Authors:	Song-Chun Zhu • Ying Nian Wu
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	356
Edition:	1st ed. 2023
ISBN-13:	978-3-03-096529-7
Categories:	Books > Science & Mathematics > Mathematics > Combinatorics & graph theory Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Computing & IT > Applications of computing > Computer modelling & simulation Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision Promotions
LSN:	3-03-096529-5
Barcode:	9783030965297

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