Context-Enhanced Information Fusion - Boosting Real-World Performance with Domain Knowledge (Hardcover, 1st ed. 2016)

This text reviews the fundamental theory and latest methods for including contextual information in fusion process design and implementation. Chapters are contributed by the foremost international experts, spanning numerous developments and applications. The book highlights high- and low-level information fusion problems, performance evaluation under highly demanding conditions, and design principles. A particular focus is placed on approaches that integrate research from different communities, emphasizing the benefit of combining different techniques to overcome the limitations of a single perspective. Features: introduces the terminology and core elements in information fusion and context; presents key themes for context-enhanced information fusion; discusses design issues in developing context-aware fusion systems; provides mathematical grounds for modeling the contextual influences in representative fusion problems; describes the fusion of hard and soft data; reviews a diverse range of applications.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Advances in Computer Vision and Pattern Recognition
Release date:	June 2016
First published:	2016
Editors:	Lauro Snidaro • Jesus Garcia • James Llinas • Erik Blasch
Dimensions:	235 x 155 x 41mm (L x W x T)
Format:	Hardcover
Pages:	703
Edition:	1st ed. 2016
ISBN-13:	978-3-319-28969-4
Categories:	Books > Computing & IT > Applications of computing > Pattern recognition Books > Computing & IT > Applications of computing > Computer modelling & simulation Books > Computing & IT > Computer software packages > Computer graphics software > General Books > Computing & IT > Applications of computing > Databases > General
LSN:	3-319-28969-1
Barcode:	9783319289694

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