Laboratoire de Génie Informatique et d’Automatique de l’Artois


Corrections and informaton fusion Belief functions and information fusion. Developments and applications.

Keywords: Belief functions, Dempster-Shafer theory, Information fusion, Contextual corrections, Data association, Decision support systems, Applications.

This work has been realized with the belief function theory (or Dempster-Shafer theory), a model for uncertainty representation which generalizes in particular the probability theory. In this model, a summary of our work related with correction mechanisms of the information provided by a source is given, as well as an application in classification. Our contributions in three applications in information fusion with belief functions are also exposed. These applications concern car to car communication, data association with belief functions, the diagnosis of the winding ageing of an electric machine.

Involved research axes:

No partner is associated with this element.


Defense took place the 04/12/2015 pm31 14:30 Prestige room - FSA - Béthune


  • Rapporteur Isabelle BLOCH Télécom ParisTech, Paris
  • Rapporteur Didier DUBOIS IRIT, Toulouse
  • Rapporteur Michèle ROMBAUT Université Joseph Fourier, Grenoble
  • Examinateur Olivier COLOT Université Lille 1
  • Examinateur Thierry DENOEUX Université de Technologie de Compiègne
  • Examinateur Gilles GONCALVES Université d'Artois
  • Examinateur Daniel JOLLY Université d'Artois
  • Advisor Eric LEFEVRE Université d'Artois