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Context-Enhanced Information Fusion

Boosting Real-World Performance with Domain Knowledge

  • Lauro Snidaro
  • Jesús García
  • James Llinas
  • Erik Blasch

Part of the Advances in Computer Vision and Pattern Recognition book series (ACVPR)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Foundations

    1. Front Matter
      Pages 1-1
    2. James Llinas, Lauro Snidaro, Jesús García, Erik Blasch
      Pages 3-23
  3. Concepts of Context for Fusion

    1. Front Matter
      Pages 25-25
    2. Galina L. Rogova, Alan N. Steinberg
      Pages 27-43
    3. James Llinas, Anne-Laure Jousselme, Geoff Gross
      Pages 45-72
    4. Erik Blasch, Chun Yang, Jesús García, Lauro Snidaro, James Llinas
      Pages 73-97
    5. Steven A. Israel, Erik Blasch
      Pages 99-124
    6. Alexander Smirnov, Tatiana Levashova, Nikolay Shilov
      Pages 125-154
  4. Systems Philosophy of Contextual Fusion

    1. Front Matter
      Pages 155-155
    2. Alan N. Steinberg, Galina L. Rogova
      Pages 157-183
    3. Jesús García, Lauro Snidaro, James Llinas
      Pages 185-203
    4. Jurgo-Soren Preden, James Llinas, Leo Motus
      Pages 205-230
    5. Benjamin Newsom, Ranjeev Mittu, Mark A. Livingston, Stephen Russell, Jonathan W. Decker, Eric Leadbetter et al.
      Pages 231-267
  5. Mathematical Characterization of Context

    1. Front Matter
      Pages 269-269
    2. Giulia Battistello, Michael Mertens, Martin Ulmke, Wolfgang Koch
      Pages 297-338
    3. Adam M. Fosbury, John L. Crassidis, Jemin George
      Pages 339-379
    4. Nurali Virani, Soumalya Sarkar, Ji-Woong Lee, Shashi Phoha, Asok Ray
      Pages 403-427
  6. Context in Hard/Soft Fusion

    1. Front Matter
      Pages 429-429
    2. Lauro Snidaro, Ingrid Visentini
      Pages 431-451
    3. Joachim Biermann, Jesús García, Ksawery Krenc, Vincent Nimier, Kellyn Rein, Lauro Snidaro
      Pages 453-477
    4. Erik Blasch, Riad I. Hammoud, Haibin Ling, Dan Shen, James Nagy, Genshe Chen
      Pages 479-505
    5. Alex J. Aved, Erik Blasch
      Pages 507-537
  7. Applications of Context Approaches to Fusion

    1. Front Matter
      Pages 539-539
    2. Erik Blasch, Pengpeng Liang, Xinchu Shi, Peiyi Li, Haibin Ling
      Pages 569-595
    3. Jesús García, Tarunraj Singh, Dirk Tenne
      Pages 597-625
    4. Juan Gómez-Romero, Jesús García, Miguel A. Patricio, Miguel A. Serrano, José M. Molina
      Pages 627-651
    5. Fernando García, Aurelio Ponz, David Martín, Arturo de la Escalera, José María Armingol
      Pages 653-674
    6. Domenico D. Bloisi, Daniele Nardi, Francesco Riccio, Francesco Trapani
      Pages 675-699
  8. Alan N. Steinberg, Galina L. Rogova
    Pages E1-E1
  9. Back Matter
    Pages 701-703

About this book

Introduction

This interdisciplinary text/reference 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 holistic approaches that integrate research from different communities, emphasizing the benefit of combining different techniques to overcome the limitations of a single perspective or approach.

 

Topics and features:

 

·         Introduces the essential terminology and core elements in information fusion and context, conveyed with the support of the JDL/DFIG data fusion model

·         Presents key themes for context-enhanced information fusion, including topics derived from target tracking, decision support and threat assessment

·         Discusses design issues in developing context-aware fusion systems, proposing several architectures optimized for context access and discovery

·         Provides mathematical grounds for modeling the contextual influences in representative fusion problems, such as sensor quality assessment, target tracking, robotics, and text analysis

·         Describes the fusion of device-generated (hard) data with human-generated (soft) data

·         Reviews a diverse range of applications where the exploitation of contextual information in the fusion process boosts system performance

 

This authoritative volume will be of great use to researchers, academics, and practitioners pursuing applications where information fusion offers a solution. The broad coverage will appeal to those involved in a variety of disciplines, from machine learning and data mining, to machine vision, decision support systems, and systems engineering.

 

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 (www.isif.org).

Keywords

Context Representation and Exploitation Data and Information Fusion Hard and Soft Fusion Intelligent Algorithms Robustness and Adaptation Situation Awareness Uncertainty Characterization

Editors and affiliations

  • Lauro Snidaro
    • 1
  • Jesús García
    • 2
  • James Llinas
    • 3
  • Erik Blasch
    • 4
  1. 1.Department Mathematics and Computer ScienceUniversity of UdineUdineItaly
  2. 2.University Carlos IIIDepartment of Computer Science and Engg. University Carlos IIIColmenarejoSpain
  3. 3.Center Multisource Info. Fusion & DeptUniv. at Buffalo, of Industrial and Engg Center Multisource Info. Fusion & DeptBuffaloUSA
  4. 4.Information DirectorateAir Force Research Laboratory Information DirectorateRomeUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-28971-7
  • Copyright Information Springer International Publishing Switzerland (outside the USA) 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-28969-4
  • Online ISBN 978-3-319-28971-7
  • Series Print ISSN 2191-6586
  • Series Online ISSN 2191-6594
  • Buy this book on publisher's site
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