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Thierry Denoeux
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A k-nearest neighbor classification rule based on Dempster-Shafer theory
T Denoeux
IEEE transactions on systems, man, and cybernetics 25 (5), 804-813, 1995
15221995
Conjunctive and disjunctive combination of belief functions induced by nondistinct bodies of evidence
T Denœux
Artificial Intelligence 172 (2-3), 234-264, 2008
5092008
A neural network classifier based on Dempster-Shafer theory
T Denoeux
IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and …, 2000
4982000
ECM: An evidential version of the fuzzy c-means algorithm
MH Masson, T Denoeux
Pattern Recognition 41 (4), 1384-1397, 2008
3992008
An evidence-theoretic k-NN rule with parameter optimization
LM Zouhal, T Denoeux
IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 1998
3791998
Analysis of evidence-theoretic decision rules for pattern classification
T Denoeux
Pattern recognition 30 (7), 1095-1107, 1997
2761997
EVCLUS: evidential clustering of proximity data
T Denœux, MH Masson
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 34 …, 2004
2742004
Maximum likelihood estimation from uncertain data in the belief function framework
T Denoeux
IEEE Transactions on knowledge and data engineering 25 (1), 119-130, 2011
2642011
Reasoning with imprecise belief structures
T Denœux
International Journal of Approximate Reasoning 20 (1), 79-111, 1999
2251999
Refined modeling of sensor reliability in the belief function framework using contextual discounting
D Mercier, B Quost, T Denœux
Information fusion 9 (2), 246-258, 2008
2112008
Initializing back propagation networks with prototypes
T Denoeux, R Lengellé
Neural Networks 6 (3), 351-363, 1993
2001993
Classification using belief functions: relationship between case-based and model-based approaches
T DenuxDenoeux, P Smets
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 36 …, 2006
1802006
Modeling vague beliefs using fuzzy-valued belief structures
T Denœux
Fuzzy sets and systems 116 (2), 167-199, 2000
1722000
Handling possibilistic labels in pattern classification using evidential reasoning
T Denœux, LM Zouhal
Fuzzy sets and systems 122 (3), 409-424, 2001
1682001
Nonparametric regression analysis of uncertain and imprecise data using belief functions
S Petit-Renaud, T Denœux
International Journal of Approximate Reasoning 35 (1), 1-28, 2004
1422004
Inferring a possibility distribution from empirical data
MH Masson, T Denoeux
Fuzzy sets and systems 157 (3), 319-340, 2006
1402006
Fault diagnosis in railway track circuits using Dempster–Shafer classifier fusion
L Oukhellou, A Debiolles, T Denœux, P Aknin
Engineering Applications of Artificial Intelligence 23 (1), 117-128, 2010
1392010
The cautious rule of combination for belief functions and some extensions
T Denœux
2006 9th International Conference on Information Fusion, 1-8, 2006
1392006
Learning from partially supervised data using mixture models and belief functions
E Côme, L Oukhellou, T Denoeux, P Aknin
Pattern recognition 42 (3), 334-348, 2009
1382009
Classifier fusion in the Dempster–Shafer framework using optimized t-norm based combination rules
B Quost, MH Masson, T Denœux
International Journal of Approximate Reasoning 52 (3), 353-374, 2011
1372011
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