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Applications of belief functions

  1. Ph. Xu, F. Davoine, J.-B. Bordes, T. Denoeux. Fusion d'informations pour la compréhension de scènes. Traitement du Signal (to appear), 2014. pdf
  2. E. Côme, L. Oukhellou, T. Denoeux and P. Aknin. Fault diagnosis of a railway device using semi-supervised independent factor analysis with mixing constraints. Pattern Analysis and Applications, Vol. 15, Number 3, Pages 313-326, 2012. pdf
  3. Z. L. Cherfi, L. Oukhellou, E. Côme, T. Denoeux and P. Aknin. Partially supervised Independent Factor Analysis using soft labels elicited from multiple experts: Application to railway track circuit diagnosis. Soft Computing, Vol. 16, Number 5, pages 741-754, 2012. pdf
  4. F. Abdallah, G. Nassreddine and T. Denoeux. A multiple-hypotheses map matching method suitable for weighted and box-shaped state estimation for localization. IEEE Transactions on Intelligent Transportation Systems, Vol. 12, Issue 4, pages 1495-1510, 2011. pdf
  5. L. Oukhellou, A. Debiolles, T. Denoeux and P. Aknin. Fault diagnosis in railway track circuits using Dempster-Shafer classifier fusion. Engineering Applications of Artificial Intelligence, Vol. 23, pages 117-128, 2010. pdf
  6. K. Worden, G. Manson, T. Denoeux. An evidence-based approach to damage location on an aircraft structure. Mechanical Systems and Signal Processing, Vol. 23, Issue 6, pages 1792-1804, 2009. pdf
  7. D. Mercier, G. Cron, T. Denoeux and M.-H. Masson. Decision fusion for postal address recognition using belief functions. Expert Systems with Applications, Vol. 36, Issue 3, pages 5643-5653, 2009. pdf
  8. D. Mercier, G. Cron, T. Denoeux and M.-H. Masson. Fusion de décisions postales dans le cadre du Modèle des Croyances Transférables. Traitement du Signal, Vol. 24, Issue 2, pages 133-151, 2007. pdf
  9. S. Démotier, W. Schön and T. Denoeux. Risk Assessment Based on Weak Information using Belief Functions: A Case Study in Water Treatment, IEEE Transactions on Systems, Man and Cybernetics C, , Vol. 36, Issue 3, 382-396, 2006. postscript, pdf

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