9783319289694-3319289691-Context-Enhanced Information Fusion: Boosting Real-World Performance with Domain Knowledge (Advances in Computer Vision and Pattern Recognition)

Context-Enhanced Information Fusion: Boosting Real-World Performance with Domain Knowledge (Advances in Computer Vision and Pattern Recognition)

ISBN-13: 9783319289694
ISBN-10: 3319289691
Edition: 1st ed. 2016
Author: Jesus Garcia, James Llinas, Erik Blasch, Lauro Snidaro
Publication date: 2016
Publisher: Springer
Format: Hardcover 721 pages
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Book details

ISBN-13: 9783319289694
ISBN-10: 3319289691
Edition: 1st ed. 2016
Author: Jesus Garcia, James Llinas, Erik Blasch, Lauro Snidaro
Publication date: 2016
Publisher: Springer
Format: Hardcover 721 pages

Summary

Context-Enhanced Information Fusion: Boosting Real-World Performance with Domain Knowledge (Advances in Computer Vision and Pattern Recognition) (ISBN-13: 9783319289694 and ISBN-10: 3319289691), written by authors Jesus Garcia, James Llinas, Erik Blasch, Lauro Snidaro, was published by Springer in 2016. With an overall rating of 3.5 stars, it's a notable title among other AI & Machine Learning (Computer Science) books. You can easily purchase or rent Context-Enhanced Information Fusion: Boosting Real-World Performance with Domain Knowledge (Advances in Computer Vision and Pattern Recognition) (Hardcover) from BooksRun, along with many other new and used AI & Machine Learning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

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.

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