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Advances in Computer Vision and Pattern Recognition

Context-Enhanced Information Fusion

Boosting Real-World Performance with Domain Knowledge

Editors: Snidaro, L., García, J., Llinas, J., Blasch, E. (Eds.)

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  • Provides a special focus on practical approaches to solving real-world problems
  • Describes the application of signal and intelligence processing approaches to open challenges in information fusion
  • Presents an holistic approach, integrating research results from different communities
  • Reviews contemporary developments on fresh and challenging topics in information fusion
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eBook $139.00
price for USA (gross)
  • ISBN 978-3-319-28971-7
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $179.99
price for USA
  • ISBN 978-3-319-28969-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $179.99
price for USA
  • ISBN 978-3-319-80464-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

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.

About the authors

Dr. Lauro Snidaro is an Assistant Professor in the Department of Mathematics and Computer Science at the University of Udine, Italy. Dr. Jesús García is an Associate Professor in the Computer Science and Engineering Department at the Carlos III University of Madrid, Spain. Dr. James Llinas is an Emeritus Professor in the Department of Industrial and Systems Engineering, and in the Department of Electrical Engineering, at the State University of New York at Buffalo, NY, USA. Dr. Erik Blasch is a Principal Scientist at the Air Force Research Laboratory Information Directorate (AFRL/RIEA) in Rome, NY, USA. The editors and contributors have all been leading experts within the international society of information fusion (ISIF).

Table of contents (26 chapters)

Table of contents (26 chapters)

Buy this book

eBook $139.00
price for USA (gross)
  • ISBN 978-3-319-28971-7
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $179.99
price for USA
  • ISBN 978-3-319-28969-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $179.99
price for USA
  • ISBN 978-3-319-80464-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.

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Bibliographic Information

Bibliographic Information
Book Title
Context-Enhanced Information Fusion
Book Subtitle
Boosting Real-World Performance with Domain Knowledge
Editors
  • Lauro Snidaro
  • Jesús García
  • James Llinas
  • Erik Blasch
Series Title
Advances in Computer Vision and Pattern Recognition
Copyright
2016
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland (outside the USA)
eBook ISBN
978-3-319-28971-7
DOI
10.1007/978-3-319-28971-7
Hardcover ISBN
978-3-319-28969-4
Softcover ISBN
978-3-319-80464-4
Series ISSN
2191-6586
Edition Number
1
Number of Pages
XVIII, 703
Number of Illustrations
13 b/w illustrations, 229 illustrations in colour
Topics