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Thierry Denoeux
Thierry Denoeux
Professor, Université de technologie de Compiègne, Institut Universitaire de France
在 utc.fr 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
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
16491995
A neural network classifier based on Dempster-Shafer theory
T Denoeux
IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and …, 2000
5712000
Conjunctive and disjunctive combination of belief functions induced by nondistinct bodies of evidence
T Denœux
Artificial Intelligence 172 (2-3), 234-264, 2008
5362008
ECM: An evidential version of the fuzzy c-means algorithm
MH Masson, T Denoeux
Pattern Recognition 41 (4), 1384-1397, 2008
4442008
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
3951998
EVCLUS: evidential clustering of proximity data
T Denœux, MH Masson
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 34 …, 2004
2942004
Analysis of evidence-theoretic decision rules for pattern classification
T Denoeux
Pattern recognition 30 (7), 1095-1107, 1997
2921997
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
2852011
Reasoning with imprecise belief structures
T Denœux
International Journal of Approximate Reasoning 20 (1), 79-111, 1999
2391999
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
2232008
Initializing back propagation networks with prototypes
T Denoeux, R Lengellé
Neural Networks 6 (3), 351-363, 1993
2081993
Decision-making with belief functions: A review
T Denoeux
International Journal of Approximate Reasoning 109, 87-110, 2019
1882019
Classification using belief functions: relationship between case-based and model-based approaches
T Denoeux, P Smets
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 36 …, 2006
1842006
Handling possibilistic labels in pattern classification using evidential reasoning
T Denœux, LM Zouhal
Fuzzy sets and systems 122 (3), 409-424, 2001
1812001
Modeling vague beliefs using fuzzy-valued belief structures
T Denœux
Fuzzy sets and systems 116 (2), 167-199, 2000
1792000
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
1602010
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
1532009
Inferring a possibility distribution from empirical data
MH Masson, T Denoeux
Fuzzy sets and systems 157 (3), 319-340, 2006
1532006
Logistic regression, neural networks and Dempster–Shafer theory: A new perspective
T Denœux
Knowledge-Based Systems 176, 54-67, 2019
1512019
Maximum likelihood estimation from fuzzy data using the EM algorithm
T Denœux
Fuzzy sets and systems 183 (1), 72-91, 2011
1512011
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