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  • Conference proceedings
  • © 2012

Belief Functions: Theory and Applications

Proceedings of the 2nd International Conference on Belief Functions, Compiègne, France 9-11 May 2012

  • Latest research on theory and applications Belief functions
  • Results of the 2nd International Conference on Belief Functions, Compiègne, France 9-11 May 2012
  • Written by leading experts in the field

Part of the book series: Advances in Intelligent and Soft Computing (AINSC, volume 164)

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Table of contents (51 papers)

  1. Front Matter

    Pages 1-9
  2. On Belief Functions and Random Sets

    • Hung T. Nguyen
    Pages 1-19
  3. Evidential Multi-label Classification Using the Random k-Label Sets Approach

    • Sawsan Kanj, Fahed Abdallah, Thierry Denœux
    Pages 21-28
  4. An Evidential Improvement for Gender Profiling

    • Jianbing Ma, Weiru Liu, Paul Miller
    Pages 29-36
  5. An Evidential Pattern Matching Approach for Vehicle Identification

    • Anne-Laure Jousselme, Patrick Maupin
    Pages 45-52
  6. A Comparison between a Bayesian Approach and a Method Based on Continuous Belief Functions for Pattern Recognition

    • Anthony Fiche, Arnaud Martin, Jean-Christophe Cexus, Ali Khenchaf
    Pages 53-60
  7. Prognostic by Classification of Predictions Combining Similarity-Based Estimation and Belief Functions

    • Emmanuel Ramasso, Michèle Rombaut, Noureddine Zerhouni
    Pages 61-68
  8. Adaptive Initialization of a EvKNN Classification Algorithm

    • Stefen Chan Wai Tim, Michèle Rombaut, Denis Pellerin
    Pages 69-76
  9. Classification Trees Based on Belief Functions

    • Nicolas Sutton-Charani, Sébastien Destercke, Thierry Denœux
    Pages 77-84
  10. Consonant Approximations in the Belief Space

    • Fabio Cuzzolin
    Pages 125-133
  11. Controling the Number of Focal Elements

    • Christophe Osswald
    Pages 135-143
  12. Random Generation of Mass Functions: A Short Howto

    • Thomas Burger, Sébastien Destercke
    Pages 145-152
  13. Revisiting the Notion of Conflicting Belief Functions

    • Sébastien Destercke, Thomas Burger
    Pages 153-160

About this book

The theory of belief functions, also known as evidence theory or Dempster-Shafer theory, was first introduced by Arthur P. Dempster in the context of statistical inference, and was later developed by Glenn Shafer as a general framework for modeling epistemic uncertainty. These early contributions have been the starting points of many important developments, including the Transferable Belief Model and the Theory of Hints. The theory of belief functions is now well established as a general framework for reasoning with uncertainty, and has well understood connections to other frameworks such as probability, possibility and imprecise probability theories.

 

This volume contains the proceedings of the 2nd International Conference on Belief Functions that was held in Compiègne, France on 9-11 May 2012. It gathers 51 contributions describing recent developments both on theoretical issues (including approximation methods, combination rules, continuous belief functions, graphical models and independence concepts) and applications in various areas including classification, image processing, statistics and intelligent vehicles.

 

Editors and Affiliations

  • , Centre de Recherches de Royallieu, Université de Technologie de Compiègne, Compiègne, France

    Thierry Denoeux

  • Université de Picardie Jules Verne, Compiègne, France

    Marie-Hélène Masson

Bibliographic Information

  • Book Title: Belief Functions: Theory and Applications

  • Book Subtitle: Proceedings of the 2nd International Conference on Belief Functions, Compiègne, France 9-11 May 2012

  • Editors: Thierry Denoeux, Marie-Hélène Masson

  • Series Title: Advances in Intelligent and Soft Computing

  • DOI: https://doi.org/10.1007/978-3-642-29461-7

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2012

  • Softcover ISBN: 978-3-642-29460-0Published: 27 April 2012

  • eBook ISBN: 978-3-642-29461-7Published: 26 April 2012

  • Series ISSN: 1867-5662

  • Series E-ISSN: 1867-5670

  • Edition Number: 1

  • Number of Pages: XII, 444

  • Number of Illustrations: 42 b/w illustrations, 54 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

Buy it now

Buying options

eBook USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access