David Mercier's Homepage

Welcome

David Mercier

Maître de Conférences (HDR) - Associate Professor - at Université d'Artois

Laboratoire de Génie Informatique et d'Automatique de l'Artois (LGI2A) - Faculté des Sciences Appliquées, Technoparc Futura, 62400 Béthune, France -

IUT de Béthune, Département R&T - 1230 rue de l'Université, CS 20819, 62408 Béthune Cedex, France -

Email / Phone

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Short Biography

I graduated in 2003 with an artificial intelligence DEA (equivalent of a M.S.) from the University Paul Sabatier (UPS) of Toulouse, France, and earned a PhD from the University of Technology of Compiègne, France (UTC) in 2006. From November 2006 to August 2007, I was an Assistant Professor (French ATER) at the UTC. Since September 2008, I am an Associate Professor at the University of Artois, France, after having been an Assistant Professor (French ATER) from September 2007 to August 2008. Since September 2012, I am an elected member of the executive board of the Belief Functions and Applications Society (Member since 2010). I obtained my French Research Habilitation (HDR) from the University of Artois in 2015. My research interests include information fusion and reasoning with uncertainty in particular with belief functions.

Publications

International Journal Articles

  1. M. Bou Farah, D. Mercier, É. Lefèvre, F. Delmotte, Methods using belief functions to manage imperfect information concerning events on the road in VANETs, Transportation Research Part C: Emerging Technologies, Vol. 67, pp. 299-320, June 2016. [pdf]
  2. F. Pichon, D. Mercier, É. Lefèvre, F. Delmotte, Proposition and learning of some belief function contextual correction mechanisms, International Journal of Approximate Reasoning, Vol. 72, pp 4-42, May 2016. [pdf]
  3. D. Mercier, F. Pichon, É. Lefèvre Corrigendum to “Belief functions contextual discounting and canonical decompositions” [International Journal of Approximate Reasoning 53 (2012) 146–158], International Journal of Approximate Reasoning, Vol. 70, pp. 137-139, March 2016. [pdf]
  4. S. Hachour, F. Delmotte, D. Mercier, É. Lefèvre, Object tracking and credal classification with kinematic data in a multi-target context, Information Fusion, Vol. 69, pp. 174-188, November 2014 [pdf]
  5. M. Bou Farah, D. Mercier, É. Lefèvre, F. Delmotte, A high-level application using belief functions for exchanging and managing uncertain events on the road in vehicular ad-hoc networks, Annals of telecommunications: special issue on belief functions and uncertainty management in networks and telecommunication, Vol. 69, Issue 3-4, pp. 185-199, April 2014. [pdf]
  6. D. Mercier, É. Lefèvre, F. Delmotte, Belief functions contextual discounting and canonical decompositions, International Journal of Approximate Reasoning, Vol. 53, Issue 2, pp. 146-158, February 2012. [pdf]
  7. D. Mercier, É. Lefèvre, D. Jolly, Object association with belief functions, an application with vehicles, Information Sciences, Vol. 181, Issue 24, pp. 5485-5500, December 2011. [pdf]
  8. F. Périsse, D. Mercier, É. Lefèvre, D. Roger, Robust diagnostics of stator insulation based on high frequency resonances measurements, IEEE Transactions on Dielectrics and Electrical Insulation, Vol. 16, Issue 5, pp. 1496-1502, October 2009. (In the electronics specialists commmunity, a collaboration with the LSEE laboratory). [pdf]
  9. D. Mercier, G. Cron, T. Denœux, M.-H. Masson, Decision fusion for postal address recognition using belief functions, Expert Systems with Applications, Vol. 36, Issue 3, pp. 5643-5653, April 2009. [pdf]
  10. D. Mercier, B. Quost, T. Denœux, Refined modeling of sensor reliability in the belief function framework using contextual discounting, Information Fusion, Vol. 9, Issue 2, pp 246-258, April 2008. [pdf]

Book Chapters

  1. S. Hachour, F. Delmotte, D. Mercier, Belief function based multisensor multitarget classification solution, Multisensor data fusion, From algorithms and architectural design to applications, H. Fourati (Ed.), CRC Press, pp. 331-348, August 2015.
  2. D. Mercier, T. Denœux, M.-H. Masson, Belief function correction mechanisms, Studies in Fuzziness and Soft Computing, B. Bouchon-Meunier et al. (Eds.), Vol. 249, pp. 203-222, January 2010. [pdf]

French-speaking Journal Articles

  1. D. Mercier, É. Lefèvre, D. Jolly, Association pour le suivi d'objets dans le cadre des fonctions de croyance, appliquée aux véhicules intelligents, Revue des Nouvelles Technologies de l'Information, Vol. E-18, pp. 25-50, Février 2010. [pdf]
  2. D. Mercier, G. Cron, T. Denœux, M.-H. Masson, Fusion de décisions postales dans le cadre du Modèle des Croyances Transférables, Traitement du Signal, vol. 24, num. 2, pp. 133-151, 2007. [pdf]

International Conference Papers

  1. P. Minary, F. Pichon, D. Mercier, É. Lefèvre, B. Droit. An Evidential Pixel-Based Face Blurring Approach, 4th International Conference on Belief Functions, BELIEF 2016, J. Vejnarová and V. Kratochvil (Eds.), pp 222-230, Prague, Czech Republic, September 21-23, 2016. (co-best student paper award) [pdf]
  2. N. Helal, F. Pichon, D. Porumbel, D. Mercier, É. Lefèvre. The Capacitated Vehicle Routing Problem with Evidential Demands : A Belief-Constrained Programming Approach, 4th International Conference on Belief Functions, BELIEF 2016, J. Vejnarová and V. Kratochvil (Eds.), pp 212-221, Prague, Czech Republic, September 21-23, 2016. [pdf]
  3. P. Minary, B. Droit, F. Pichon, D. Mercier, É. Lefèvre. A fusion method for blurring faces on platforms using belief functions, 11th World Congress on Railway Research, Milan, Italy, May 29-June 2, 2016. [pdf]
  4. D. Mercier, F. Pichon, É. Lefèvre, F. Delmotte, Learning contextual discounting and contextual reinforcement from labelled data, 13th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2015, S. Destercke and T. Denœux (Eds), LNAI 9161, pp. 472-481, Compiègne, France, July 15-17, 2015. [pdf]
  5. F. Pichon, D. Mercier, F. Delmotte, É. Lefèvre, Truthfulness in contextual information correction, 3rd International Conference on Belief Functions, BELIEF 2014, F. Cuzzolin (Ed.), pp. 11-20, Oxford, United Kingdom, September 26-28, 2014. [pdf]
  6. M. Bou Farah, D. Mercier, F. Delmotte, É. Lefèvre, S. Lagrue, Methods handling accident and traffic jam information with belief functions in VANETs, 3rd International Conference on Belief Functions, BELIEF 2014, F. Cuzzolin (Ed.), pp. 124-133, Oxford, United Kingdom, September 26-28, 2014. [pdf]
  7. S. Hachour, F. Delmotte, D. Mercier, A new parameterless credal method to track-to-track assignment problem, 3rd International Conference on Belief Functions, BELIEF 2014, F. Cuzzolin (Ed.), pp. 403-411, Oxford, United Kingdom, September 26-28, 2014. [pdf]
  8. F. Delmotte, D. Mercier, F. Pichon, A first inquiry into Simpson's paradox with belief functions, 15th Information Processing and Management of Uncertainty in Knowledge-Based Systems International Conference, IPMU 2014, pp. 190-199, Montpellier, France, July 15-19, 2014. [pdf]
  9. S. Hachour, F. Delmotte, D. Mercier, Comparison of credal assignment algorithms in kinematic data tracking context, 15th Information Processing and Management of Uncertainty in Knowledge-Based Systems International Conference, IPMU 2014, pp. 200-211, Montpellier, France, July 15-19, 2014. [pdf]
  10. S. Hachour, F. Delmotte, D. Mercier, A distributed solution for multi-object tracking and classification, 17th International Conference on Information Fusion, FUSION 2014, paper 323, Salamanca, Spain, July 7-10, 2014. [pdf]
  11. S. Hachour, F. Delmotte, D. Mercier, É. Lefèvre, Multi-sensor multi-target tracking with robust kinematic data based credal classification, 8th Workshop, Sensor Data Fusion: Trends, Solutions, Application, SDF 2013, paper Thu1130, Bonn, Germany, October 9-11, 2013. [pdf]
  12. M. Bou Farah, D. Mercier, É. Lefèvre, F. Delmotte, Exchanging dynamic and imprecise information in V2V networks with belief functions, 16th International IEEE Conference on Intelligent Transport Systems, ITSC 2013, pp. 967-972, The Hague, The Netherlands, October 6-9, 2013 [pdf] [pres]
  13. R. Pusca, C. Demian, D. Mercier, É. Lefèvre, R. Romary, An improvement of a diagnosis procedure for AC machines using two external flux sensors based on a fusion process with belief functions, 38th Annual Conference of the IEEE Industrial Electronics Society, IECON 2012, pp. 5078-5083, Montréal, Québec, Canada, October 25-28, 2012. [pdf]
  14. É. Lefèvre, Z. Elouedi, D. Mercier, Towards an alarm for opposition conflict in a conjunctive combination of belief functions, 11th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2011, LNAI 6717, pp. 314-325, Belfast, Northern Ireland, UK, June 29 - July 1, 2011. [pdf]
  15. M. Bou Farah, D. Mercier, É. Lefèvre, F. Delmotte, Towards a robust exchange of imperfect information in inter-vehicle ad-hoc networks using belief functions, IEEE Intelligent Vehicles Symposium, IV 2011, pp. 436-441, Baden-Baden, Germany, June 5-9, 2011. [pdf] [poster]
  16. Z. Elouedi, É. Lefèvre, D. Mercier, Discountings of a belief function using a confusion matrix, 22th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2010, Vol. 1, pp. 287-294, Arras, France, October 27-29, 2010. [pdf]
  17. D. Mercier, Extending the contextual discounting of a belief function thanks to its canonical disjunctive decomposition, 1st Workshop on Belief Functions, BELIEF 2010, paper 61, Brest, France, April 1-2, 2010. [pdf]
  18. D. Mercier, É. Lefèvre, D. Jolly, Object association in the TBM framework, application to vehicle driving aid, 6th International Symposium on Imprecise Probability: Theories and Applications, ISIPTA 2009, pp. 317-326, Durham, United Kingdom, July 14-18, 2009. [pdf]
  19. A. Veremme, É. Lefèvre, D. Dupont, D. Mercier, Belief assignment on compound hypotheses within the framework of the Transferable Belief Model, 12th International Conference on Information Fusion, FUSION 2009, paper 0203, Seattle, USA, July 6-9, 2009. [pdf]
  20. D. Mercier, T. Denœux, M.-H. Masson, A parametrized family of belief functions correction mechanisms, 12th Information Processing and Management of Uncertainty in Knowledge-Based Systems International Conference, IPMU 2008, pp. 306-313, Malaga, Spain, June 22-27, 2008. [pdf]
  21. F. Périsse, É. Lefèvre, D. Mercier, D. Roger, E. Matéo, Diagnostic based on high frequency resonances and information fusion, 17th IEEE International Symposium on Electrical Insulation, ISEI 2008, pp. 628-631, Vancouver, Canada, June 8-11, 2008. [pdf]
  22. D. Mercier, T. Denœux, M.-H. Masson, General correction mechanisms for weakening or reinforcing belief functions, 9th International Conference on Information Fusion, FUSION 2006, article 146, Florence, Italy, July 10-13, 2006. [pdf]
  23. D. Mercier, T. Denœux, M.-H. Masson, Refined sensor tuning in the belief function framework using contextual discounting, 11th Information Processing and Management of Uncertainty in Knowledge-Based Systems International Conference, IPMU 2006, pp. 1443-1450, Paris, France, July 2-7, 2006. [pdf]
  24. D. Mercier, G. Cron, T. Denœux, M.-H. Masson, Fusion of multi-level decision systems using the Transferable Belief Model, 8th International Conference on Information Fusion, article C8-2, FUSION 2005, Philadelphia, USA, July 25-29, 2005. [pdf]
  25. D. Mercier, B. Quost, T. Denœux, Contextual discounting of belief functions, 8th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2005, pp. 552-562, Barcelona, Spain, July 6-8, 2005. [pdf]

French-speaking Conference Papers

  1. N. Helal, F. Pichon, D. Porumbel, D. Mercier, É. Lefèvre, Optimisation discrète sous incertitudes modélisées par des fonctions de croyance, 17ème congrès ROADEF de la société Française de Recherche Opérationnelle et Aide à la Décision, Compiègne, France, 10-12 Février, 2016. [pdf]
  2. É. Lefèvre, F. Pichon, D. Mercier, E. Elouedi, B. Quost, Estimation de méta-connaissances à partir de matrices de confusion pour la correction de fonctions de croyance, 23e Rencontres Francophones sur la Logique Floue et ses Applications, LFA 2014, pp. 115-122, Cargèse, France, 22-24 Octobre, 2014. [pdf]
  3. S. Hachour, F. Delmotte, D. Mercier, É. Lefèvre, Fusion d'informations pour la classification multi-capteurs, multi-cibles, 22e Rencontres Francophones sur la Logique Floue et ses Applications, LFA 2013, pp. 111-118, Reims, France, 10-11 Octobre, 2013. [pdf]
  4. S. Hachour, F. Delmotte, É. Lefèvre, D. Mercier. Tracking and Identification of Multiple targets. 7e Workshop Interdisciplinaire sur la Sécurité Globale, WISG 2013, papier 13, Troyes, France, 22-23 Janvier, 2013. [pdf] [poster]
  5. M. Bou Farah, D. Mercier, É. Lefèvre, F. Delmotte, Un processus V2V d'échanges et de gestion d'informations imparfaites basé sur des fonctions de croyance, 21e Rencontres Francophones sur la Logique Floue et ses Applications, LFA 2012, pp. 71-78, Compiègne, France, 15-16 Novembre, 2012. [pdf]
  6. S. Hachour, F. Delmotte, É. Lefèvre, D. Mercier, J. Klein, J.M. Vannobel, Classification crédale multi-cibles, 21e Rencontres Francophones sur la Logique Floue et ses Applications, LFA 2012, pp. 201-208, Compiègne, France, 15-16 Novembre, 2012. [pdf]
  7. D. Mercier, É. Lefèvre, R. Pusca, C. Demian, R. Romary, Étude préliminaire de l'application de la fusion d'informations pour le diagnostic de défauts de bobinages de machines à courant alternatif, 21e Rencontres Francophones sur la Logique Floue et ses Applications, LFA 2012, pp. 87-94, Compiègne, France, 15-16 Novembre, 2012. [pdf]
  8. D. Mercier, Z. Elouedi, É. Lefèvre, Sur l'affaiblissement d'une fonction de croyance par une matrice de confusion, 19e Rencontres Francophones sur la Logique Floue et ses Applications, LFA 2010, pp. 277-283, Lannion, France, 18-19 Novembre, 2010. [pdf]
  9. G. Morvan, A. Veremme, D. Mercier, É. Lefèvre, Application du Modèle des Croyances Transférables dans le cadre d'expertises en Entomologie Médico-Légale, 5e atelier sur la Fouille de données complexes dans un processus d'extraction des connaissances des 8e journées francophones Extraction et Gestion des Connaissances, pp. 49-60, 29 janvier, Nice, 2008. [pdf]
  10. D. Mercier, G. Cron, T. Denœux, M.-H. Masson, Une Approche Globale de Fusion d'Adresses Postales Basée sur la Théorie des Fonctions de Croyance, 15e Rencontres Francophones sur la Logique Floue et ses Applications, LFA 2006, pp. 287-294, Toulouse, France, 19-20 Octobre, 2006. [pdf]
  11. D. Mercier, G. Cron, T. Denœux, M.-H. Masson, Vers un Modèle de Fusion de Décisions de Lecteurs d'Adresses Postales Basé sur la Théorie des Fonctions de Croyance, 9e Colloque International Francophone sur l'Écrit et le Document, CIFED 2006, pp. 79-84, Fribourg, Suisse, 18-21 Septembre, 2006. [pdf]
  12. L. Amgoud, A. Herzig, D. Mercier, Calcul des intentions d'agent à partir de ses désirs, 2e Conférence Modèles Formels d'Interaction, MFI 2003, pp 3-9, Lille, France, 20-23 mai, 2003. (Realized during my DEA, equivalent of a M.S. in the IRIT laboratory of Toulouse) [pdf]

Scientific Patents

  1. D. Mercier, G. Cron, B. Benyoub, Method of merging postal OCR using credibility functions, European Patent Application EP1835444, september 19th, 2007.
  2. D. Mercier, G. Cron, B. Benyoub, Méthode pour fusionner des OCR postaux exploitant des fonctions de croyance, Brevet n°FR 0650910, 17 mars 2006.

Mémoire scientifique HDR (In French)

  1. D. Mercier, Corrections et fusion d'informations dans le cadre des fonctions de croyance. Applications., defended on December 4th, 2015. [pdf,slides] Supervisor: É. Lefèvre.

Ph.D. Thesis (In French)

  1. D. Mercier, Fusion d'informations pour la reconnaissance automatique d'adresses postales dans le cadre de la théorie des fonctions de croyance, defended on December 6th, 2006. [pdf,slides,pres.] Supervisors: T. Denœux and M.-H. Masson.

Ph.D. Students

As co-supervisor ("co-encadrant" in French):

Defended

  1. S. Hachour. Suivi et classification d'objets multiples : contributions avec la théorie des fonctions de croyance, supervisor: F. Delmotte, defended on June 5th, 2015 [pdf, slides]
  2. M. Bou Farah. Méthodes utilisant des fonctions de croyance pour la gestion des informations imparfaites dans les réseaux de véhicules, supervisor: F. Delmotte, defended on December 2nd, 2014 [pdf, slides]

In progress

  1. P. Minary. Détection et suivi de visages sur des images vidéo à l'aide de la théorie des fonctions de croyance, supervisor: É. Lefèvre, co-supervisor: F. Pichon, defense expected on December 2017.

Talks

  1. D. Mercier, On belief function corrections, 3rd School on belief functions and their applications, Stella Plage, France, September 28th - October 2nd, 2015 [pdf]
  2. D. Mercier, Five-minute talk on the Transferable Belief Model, Uncertainty Forum, Fusion 2010, Edinburgh July 26-29 2010 [pdf]
  3. D. Mercier, Autour des mécanismes de correction de fonctions de croyance, des décompositions canoniques et de l'association d'objets, Séminaire LAGIS Lille, 9 juillet 2010 [pdf]
  4. D. Mercier, Autour des mécanismes de correction de fonctions de croyance, Réunion GDR ISIS - Avancées en Fusion de données - 11 février 2010 [pdf]
  5. D. Mercier, Fusion d'informations imparfaites, Petit Déjeuner Scientifique, IRSAA, 31 mars 2009 [(vulgarisation) pdf]
  6. D. Mercier, Le Modèle des Croyances Transférables : une interprétation de la théorie des fonctions de croyance, Séminaire LGI2A Béthune, 13 novembre 2007 [pdf]

Teaching

  1. Master Recherche Génie Industriel et Logistique, Concepts de base de la théorie des fonctions de croyance (in French) : [ lesson ] [ td ] [ tp ]