Hybrid Soft Computing for Image Segmentation (Hardcover, 1st ed. 2016)

This book proposes soft computing techniques for segmenting real-life images in applications such as image processing, image mining, video surveillance, and intelligent transportation systems. The book suggests hybrids deriving from three main approaches: fuzzy systems, primarily used for handling real-life problems that involve uncertainty; artificial neural networks, usually applied for machine cognition, learning, and recognition; and evolutionary computation, mainly used for search, exploration, efficient exploitation of contextual information, and optimization. The contributed chapters discuss both the strengths and the weaknesses of the approaches, and the book will be valuable for researchers and graduate students in the domains of image processing and computational intelligence.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	November 2016
First published:	2016
Editors:	Siddhartha Bhattacharyya • Paramartha Dutta • Sourav De • Goran Klepac
Dimensions:	235 x 155 x 21mm (L x W x T)
Format:	Hardcover
Pages:	321
Edition:	1st ed. 2016
ISBN-13:	978-3-319-47222-5
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks Books > Computing & IT > Applications of computing > Image processing > General
LSN:	3-319-47222-4
Barcode:	9783319472225

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