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ORCIDThierry Denoeux
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- affiliation: Université de technologie de Compiègne, France
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2020 – today
- 2023
[j119]Thierry Denoeux
:
Reasoning with fuzzy and uncertain evidence using epistemic random fuzzy sets: General framework and practical models. Fuzzy Sets Syst. 453: 1-36 (2023)- [j118]Thierry Denoeux:
Parametric families of continuous belief functions based on generalized Gaussian random fuzzy numbers. Fuzzy Sets Syst. 471: 108679 (2023) - [j117]Ling Huang, Su Ruan, Thierry Denoeux:
Semi-supervised multiple evidence fusion for brain tumor segmentation. Neurocomputing 535: 40-52 (2023) - [j116]Ling Huang, Su Ruan, Thierry Denoeux:
Application of belief functions to medical image segmentation: A review. Inf. Fusion 91: 737-756 (2023) - [j115]Andrea Campagner, Davide Ciucci, Thierry Denoeux:
A general framework for evaluating and comparing soft clusterings. Inf. Sci. 623: 70-93 (2023) - [i22]Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux:
Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation. CoRR abs/2309.05919 (2023) - 2022
- [j114]Lianmeng Jiao, Thierry Denoeux, Zhun-ga Liu, Quan Pan:
EGMM: An evidential version of the Gaussian mixture model for clustering. Appl. Soft Comput. 129: 109619 (2022) - [j113]John C. Aldrich, A. Philip Dawid, Thierry Denoeux, Prakash P. Shenoy, Vladimir Vovk:
Probability and statistics: Foundations and history. Special Issue in honor of Glenn Shafer. Int. J. Approx. Reason. 141: 1-4 (2022) - [j112]John C. Aldrich, A. Philip Dawid, Thierry Denoeux, Prakash P. Shenoy, Vladimir Vovk:
Glenn Shafer - A short biography. Int. J. Approx. Reason. 141: 5-10 (2022) - [j111]Andrea Campagner, Davide Ciucci, Thierry Denoeux:
Belief functions and rough sets: Survey and new insights. Int. J. Approx. Reason. 143: 192-215 (2022) - [j110]Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux:
Lymphoma segmentation from 3D PET-CT images using a deep evidential network. Int. J. Approx. Reason. 149: 39-60 (2022) - [c104]Wei Liu, Xiaodong Yue, Yufei Chen, Thierry Denoeux:
Trusted Multi-View Deep Learning with Opinion Aggregation. AAAI 2022: 7585-7593 - [c103]Andrea Campagner, Davide Ciucci, Thierry Denoeux:
A Distributional Approach for Soft Clustering Comparison and Evaluation. BELIEF 2022: 3-12 - [c102]Thierry Denoeux:
An Evidential Neural Network Model for Regression Based on Random Fuzzy Numbers. BELIEF 2022: 57-66 - [c101]Haijie Fu, Xiaodong Yue, Wei Liu, Thierry Denoeux:
Stable Clustering Ensemble Based on Evidence Theory. ICIP 2022: 2046-2050 - [c100]Ling Huang, Thierry Denoeux, Pierre Vera, Su Ruan:
Evidence Fusion with Contextual Discounting for Multi-modality Medical Image Segmentation. MICCAI (5) 2022: 401-411 - [i21]Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux:
Lymphoma segmentation from 3D PET-CT images using a deep evidential network. CoRR abs/2201.13078 (2022) - [i20]Thierry Denoeux:
Reasoning with fuzzy and uncertain evidence using epistemic random fuzzy sets: general framework and practical models. CoRR abs/2202.08081 (2022) - [i19]Andrea Campagner, Davide Ciucci, Thierry Denoeux:
A Distributional Approach for Soft Clustering Comparison and Evaluation. CoRR abs/2206.09827 (2022) - [i18]Ling Huang, Thierry Denoeux, Pierre Vera, Su Ruan:
Evidence fusion with contextual discounting for multi-modality medical image segmentation. CoRR abs/2206.11739 (2022) - [i17]Thierry Denoeux:
An Evidential Neural Network Model for Regression Based on Random Fuzzy Numbers. CoRR abs/2208.00647 (2022) - 2021
- [j109]Zheng Tong, Philippe Xu, Thierry Denoeux:
Evidential fully convolutional network for semantic segmentation. Appl. Intell. 51(9): 6376-6399 (2021) - [j108]Thierry Denoeux:
Belief functions induced by random fuzzy sets: A general framework for representing uncertain and fuzzy evidence. Fuzzy Sets Syst. 424: 63-91 (2021) - [j107]Jianxu Liu, Songsak Sriboonchitta, Aree Wiboonpongse, Thierry Denoeux:
A trivariate Gaussian copula stochastic frontier model with sample selection. Int. J. Approx. Reason. 137: 181-198 (2021) - [j106]Zheng Tong, Philippe Xu, Thierry Denoeux:
An evidential classifier based on Dempster-Shafer theory and deep learning. Neurocomputing 450: 275-293 (2021) - [j105]Thierry Denoeux:
Distributed combination of belief functions. Inf. Fusion 65: 179-191 (2021) - [j104]Thierry Denoeux:
NN-EVCLUS: Neural network-based evidential clustering. Inf. Sci. 572: 297-330 (2021) - [j103]Liyao Ma, Thierry Denoeux:
Partial classification in the belief function framework. Knowl. Based Syst. 214: 106742 (2021) - [j102]Zhi-gang Su, Qinghua Hu, Thierry Denoeux:
A Distributed Rough Evidential K-NN Classifier: Integrating Feature Reduction and Classification. IEEE Trans. Fuzzy Syst. 29(8): 2322-2335 (2021) - [j101]Zhunga Liu, Linqing Huang, Kuang Zhou, Thierry Denoeux:
Combination of Transferable Classification With Multisource Domain Adaptation Based on Evidential Reasoning. IEEE Trans. Neural Networks Learn. Syst. 32(5): 2015-2029 (2021) - [c99]Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux:
Evidential Segmentation of 3D PET/CT Images. BELIEF 2021: 159-167 - [c98]Zheng Tong, Philippe Xu, Thierry Denoeux:
Fusion of Evidential CNN Classifiers for Image Classification. BELIEF 2021: 168-176 - [c97]Ling Huang, Su Ruan, Thierry Denoeux:
Covid-19 Classification with Deep Neural Network and Belief Functions. BIBE 2021: 3:1-3:4 - [c96]Xiaoqian Zhou, Xiaodong Yue, Zhikang Xu, Thierry Denoeux, Yufei Chen:
Deep Neural Networks with Prior Evidence for Bladder Cancer Staging. BIBM 2021: 1221-1226 - [c95]Ling Huang, Su Ruan, Thierry Denoeux:
Belief Function-Based Semi-Supervised Learning For Brain Tumor Segmentation. ISBI 2021: 160-164 - [c94]Ling Huang, Thierry Denoeux, David Tonnelet, Pierre Decazes, Su Ruan:
Deep PET/CT Fusion with Dempster-Shafer Theory for Lymphoma Segmentation. MLMI@MICCAI 2021: 30-39 - [e10]Thierry Denoeux, Eric Lefèvre, Zhunga Liu, Frédéric Pichon:
Belief Functions: Theory and Applications - 6th International Conference, BELIEF 2021, Shanghai, China, October 15-19, 2021, Proceedings. Lecture Notes in Computer Science 12915, Springer 2021, ISBN 978-3-030-88600-4 [contents] - [i16]Ling Huang, Su Ruan, Thierry Denoeux:
Covid-19 classification with deep neural network and belief functions. CoRR abs/2101.06958 (2021) - [i15]Ling Huang, Su Ruan, Thierry Denoeux:
Belief function-based semi-supervised learning for brain tumor segmentation. CoRR abs/2102.00097 (2021) - [i14]Zheng Tong, Philippe Xu, Thierry Denoeux:
Evidential fully convolutional network for semantic segmentation. CoRR abs/2103.13544 (2021) - [i13]Zheng Tong, Philippe Xu, Thierry Denoeux:
An evidential classifier based on Dempster-Shafer theory and deep learning. CoRR abs/2103.13549 (2021) - [i12]Ling Huang, Su Ruan, Pierre Decazes, Thierry Denoeux:
Evidential segmentation of 3D PET/CT images. CoRR abs/2104.13293 (2021) - [i11]Ling Huang, Thierry Denoeux, David Tonnelet, Pierre Decazes, Su Ruan:
Deep PET/CT fusion with Dempster-Shafer theory for lymphoma segmentation. CoRR abs/2108.05422 (2021) - [i10]Zheng Tong, Philippe Xu, Thierry Denoeux:
Fusion of evidential CNN classifiers for image classification. CoRR abs/2108.10233 (2021) - [i9]Emmanuel Ramasso, Thierry Denoeux, Gaël Chevallier:
Clustering acoustic emission data streams with sequentially appearing clusters using mixture models. CoRR abs/2108.11211 (2021) - 2020
- [j100]Feng Li, Shoumei Li, Thierry Denoeux:
Combining clusterings in the belief function framework. Array 6: 100018 (2020) - [j99]Thierry Denoeux, Prakash P. Shenoy:
An interval-valued utility theory for decision making with Dempster-Shafer belief functions. Int. J. Approx. Reason. 124: 194-216 (2020) - [j98]Thierry Denoeux:
Calibrated model-based evidential clustering using bootstrapping. Inf. Sci. 528: 17-45 (2020) - [c93]Bin Yuan, Xiaodong Yue, Ying Lv, Thierry Denoeux:
Evidential Deep Neural Networks for Uncertain Data Classification. KSEM (2) 2020: 427-437 - [i8]Thierry Denoeux:
Belief functions induced by random fuzzy sets: Application to statistical inference. CoRR abs/2004.11638 (2020) - [i7]Thierry Denoeux:
NN-EVCLUS: Neural Network-based Evidential Clustering. CoRR abs/2009.12795 (2020) - [i6]Lianmeng Jiao, Thierry Denoeux, Zhun-ga Liu, Quan Pan:
EGMM: an Evidential Version of the Gaussian Mixture Model for Clustering. CoRR abs/2010.01333 (2020)
2010 – 2019
- 2019
- [j97]Thierry Denoeux:
Editorial: Opening up computer science. Array 1-2: 100005 (2019) - [j96]Thierry Denoeux:
Decision-making with belief functions: A review. Int. J. Approx. Reason. 109: 87-110 (2019) - [j95]Thierry Denoeux, Orakanya Kanjanatarakul, Songsak Sriboonchitta:
A new evidential K-nearest neighbor rule based on contextual discounting with partially supervised learning. Int. J. Approx. Reason. 113: 287-302 (2019) - [j94]Thierry Denoeux:
Logistic regression, neural networks and Dempster-Shafer theory: A new perspective. Knowl. Based Syst. 176: 54-67 (2019) - [j93]Zhi-gang Su, Thierry Denoeux:
BPEC: Belief-Peaks Evidential Clustering. IEEE Trans. Fuzzy Syst. 27(1): 111-123 (2019) - [j92]Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera:
Joint Tumor Segmentation in PET-CT Images Using Co-Clustering and Fusion Based on Belief Functions. IEEE Trans. Image Process. 28(2): 755-766 (2019) - [c92]Thierry Denoeux, Orakanya Kanjanatarakul:
Multistep Prediction using Point-Cloud Approximation of Continuous Belief Functions. FUZZ-IEEE 2019: 1-6 - [c91]Yixuan Qiao, Shoumei Li, Thierry Denoeux:
Collaborative Evidential Clustering. IFSA/NAFIPS 2019: 518-530 - [c90]Thierry Denoeux, Prakash P. Shenoy:
An Axiomatic Utility Theory for Dempster-Shafer Belief Functions. ISIPTA 2019: 145-155 - [c89]Liyao Ma, Thierry Denoeux:
Making Set-Valued Predictions in Evidential Classification: A Comparison of Different Approaches. ISIPTA 2019: 276-285 - [c88]Zheng Tong, Philippe Xu, Thierry Denoeux:
ConvNet and Dempster-Shafer Theory for Object Recognition. SUM 2019: 368-381 - [p5]Frédéric Pichon, Didier Dubois, Thierry Denoeux:
Quality of Information Sources in Information Fusion. Information Quality in Information Fusion and Decision Making 2019: 31-49 - [e9]Sébastien Destercke, Thierry Denoeux, María Angeles Gil, Przemyslaw Grzegorzewski, Olgierd Hryniewicz:
Uncertainty Modelling in Data Science, SMPS 2018, Compiègne, France, 17-21 September 2018. Advances in Intelligent Systems and Computing 832, Springer 2019, ISBN 978-3-319-97546-7 [contents] - [i5]Thierry Denoeux:
Calibrated model-based evidential clustering using bootstrapping. CoRR abs/1912.06137 (2019) - [i4]Thierry Denoeux, Prakash P. Shenoy:
An Interval-Valued Utility Theory for Decision Making with Dempster-Shafer Belief Functions. CoRR abs/1912.06594 (2019) - [i3]Zied Bouraoui, Antoine Cornuéjols, Thierry Denoeux, Sébastien Destercke, Didier Dubois, Romain Guillaume, João Marques-Silva, Jérôme Mengin, Henri Prade, Steven Schockaert, Mathieu Serrurier, Christel Vrain:
From Shallow to Deep Interactions Between Knowledge Representation, Reasoning and Machine Learning (Kay R. Amel group). CoRR abs/1912.06612 (2019) - 2018
- [j91]Thierry Denoeux, Shoumei Li:
Frequency-calibrated belief functions: Review and new insights. Int. J. Approx. Reason. 92: 232-254 (2018) - [j90]Liqi Sui, Pierre Feissel, Thierry Denoeux:
Identification of elastic properties in the belief function framework. Int. J. Approx. Reason. 101: 69-87 (2018) - [j89]Zhi-gang Su, Thierry Denoeux, Yong-sheng Hao, Ming Zhao:
Evidential K-NN classification with enhanced performance via optimizing a class of parametric conjunctive t-rules. Knowl. Based Syst. 142: 7-16 (2018) - [j88]Feng Li, Shoumei Li, Thierry Denoeux:
k-CEVCLUS: Constrained evidential clustering of large dissimilarity data. Knowl. Based Syst. 142: 29-44 (2018) - [j87]Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera:
Spatial Evidential Clustering With Adaptive Distance Metric for Tumor Segmentation in FDG-PET Images. IEEE Trans. Biomed. Eng. 65(1): 21-30 (2018) - [j86]Thierry Denoeux, Shoumei Li, Songsak Sriboonchitta:
Evaluating and Comparing Soft Partitions: An Approach Based on Dempster-Shafer Theory. IEEE Trans. Fuzzy Syst. 26(3): 1231-1244 (2018) - [c87]Thierry Denoeux:
Logistic Regression Revisited: Belief Function Analysis. BELIEF 2018: 57-64 - [c86]Orakanya Kanjanatarakul, Siwarat Kuson, Thierry Denoeux:
An Evidential K-Nearest Neighbor Classifier Based on Contextual Discounting and Likelihood Maximization. BELIEF 2018: 155-162 - [p4]Thierry Denoeux:
Quantifying Predictive Uncertainty Using Belief Functions: Different Approaches and Practical Construction. Predictive Econometrics and Big Data 2018: 157-176 - [e8]Sébastien Destercke, Thierry Denoeux, Fabio Cuzzolin, Arnaud Martin:
Belief Functions: Theory and Applications - 5th International Conference, BELIEF 2018, Compiègne, France, September 17-21, 2018, Proceedings. Lecture Notes in Computer Science 11069, Springer 2018, ISBN 978-3-319-99382-9 [contents] - [e7]Van-Nam Huynh, Masahiro Inuiguchi, Dang Hung Tran, Thierry Denoeux:
Integrated Uncertainty in Knowledge Modelling and Decision Making - 6th International Symposium, IUKM 2018, Hanoi, Vietnam, March 15-17, 2018, Proceedings. Lecture Notes in Computer Science 10758, Springer 2018, ISBN 978-3-319-75428-4 [contents] - [i2]Thierry Denoeux:
Logistic Regression, Neural Networks and Dempster-Shafer Theory: a New Perspective. CoRR abs/1807.01846 (2018) - [i1]Thierry Denoeux:
Decision-Making with Belief Functions: a Review. CoRR abs/1808.05322 (2018) - 2017
- [j85]Benjamin Quost, Thierry Denoeux, Shoumei Li:
Parametric classification with soft labels using the evidential EM algorithm: linear discriminant analysis versus logistic regression. Adv. Data Anal. Classif. 11(4): 659-690 (2017) - [j84]Jean-Baptiste Bordes, Franck Davoine, Philippe Xu, Thierry Denoeux:
Evidential grammars: A compositional approach for scene understanding. Application to multimodal street data. Appl. Soft Comput. 61: 1173-1185 (2017) - [j83]Songsak Sriboonchitta, Jianxu Liu, Aree Wiboonpongse, Thierry Denoeux:
A double-copula stochastic frontier model with dependent error components and correction for sample selection. Int. J. Approx. Reason. 80: 174-184 (2017) - [c85]Feng Li, Shoumei Li, Nana Tang, Thierry Denoeux:
Constrained interval-valued linear regression model. FUSION 2017: 1-8 - [c84]Chunfeng Lian, Su Ruan, Thierry Denoeux, Yu Guo, Pierre Vera:
Accurate tumor segmentation in FDG-PET images with guidance of complementary CT images. ICIP 2017: 4447-4451 - [c83]Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera:
Tumor delineation in FDG-PET images using a new evidential clustering algorithm with spatial regularization and adaptive distance metric. ISBI 2017: 1177-1180 - [c82]Orakanya Kanjanatarakul, Thierry Denoeux:
Distributed data fusion in the dempster-shafer framework. SoSE 2017: 1-6 - 2016
- [j82]Benjamin Quost, Thierry Denoeux:
Clustering and classification of fuzzy data using the fuzzy EM algorithm. Fuzzy Sets Syst. 286: 134-156 (2016) - [j81]Philippe Xu, Franck Davoine, Hongbin Zha, Thierry Denoeux:
Evidential calibration of binary SVM classifiers. Int. J. Approx. Reason. 72: 55-70 (2016) - [j80]Orakanya Kanjanatarakul, Thierry Denoeux, Songsak Sriboonchitta:
Prediction of future observations using belief functions: A likelihood-based approach. Int. J. Approx. Reason. 72: 71-94 (2016) - [j79]Thierry Denoeux:
40 years of Dempster-Shafer theory. Int. J. Approx. Reason. 79: 1-6 (2016) - [j78]Thierry Denoeux, Songsak Sriboonchitta, Orakanya Kanjanatarakul:
Evidential clustering of large dissimilarity data. Knowl. Based Syst. 106: 179-195 (2016) - [j77]Chunfeng Lian, Su Ruan, Thierry Denoeux, Fabrice Jardin, Pierre Vera:
Selecting radiomic features from FDG-PET images for cancer treatment outcome prediction. Medical Image Anal. 32: 257-268 (2016) - [j76]Philippe Xu, Franck Davoine, Jean-Baptiste Bordes, Huijing Zhao, Thierry Denoeux:
Multimodal information fusion for urban scene understanding. Mach. Vis. Appl. 27(3): 331-349 (2016) - [j75]Sawsan Kanj, Fahed Abdallah, Thierry Denoeux, Kifah Tout:
Editing training data for multi-label classification with the k-nearest neighbor rule. Pattern Anal. Appl. 19(1): 145-161 (2016) - [j74]Marie-Hélène Masson, Sébastien Destercke, Thierry Denoeux:
Modelling and predicting partial orders from pairwise belief functions. Soft Comput. 20(3): 939-950 (2016) - [j73]Chunfeng Lian, Su Ruan, Thierry Denoeux:
Dissimilarity Metric Learning in the Belief Function Framework. IEEE Trans. Fuzzy Syst. 24(6): 1555-1564 (2016) - [j72]Lianmeng Jiao, Thierry Denoeux, Quan Pan:
A Hybrid Belief Rule-Based Classification System Based on Uncertain Training Data and Expert Knowledge. IEEE Trans. Syst. Man Cybern. Syst. 46(12): 1711-1723 (2016) - [c81]Orakanya Kanjanatarakul, Songsak Sriboonchitta, Thierry Denoeux:
k-EVCLUS: Clustering Large Dissimilarity Data in the Belief Function Framework. BELIEF 2016: 105-112 - [c80]Liqi Sui, Pierre Feissel, Thierry Denoeux:
Identification of Elastic Properties Based on Belief Function Inference. BELIEF 2016: 182-189 - [c79]Chunfeng Lian, Su Ruan, Thierry Denoeux:
Joint Feature Transformation and Selection Based on Dempster-Shafer Theory. IPMU (1) 2016: 253-261 - [c78]Thierry Denoeux, Orakanya Kanjanatarakul:
Evidential Clustering: A Review. IUKM 2016: 24-35 - [c77]Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera:
Robust Cancer Treatment Outcome Prediction Dealing with Small-Sized and Imbalanced Data from FDG-PET Images. MICCAI (2) 2016: 61-69 - [c76]Thierry Denoeux, Orakanya Kanjanatarakul:
Beyond Fuzzy, Possibilistic and Rough: An Investigation of Belief Functions in Clustering. SMPS 2016: 157-164 - [e6]Van-Nam Huynh, Masahiro Inuiguchi, Bac Le, Bao Nguyen Le, Thierry Denoeux:
Integrated Uncertainty in Knowledge Modelling and Decision Making - 5th International Symposium, IUKM 2016, Da Nang, Vietnam, November 30 - December 2, 2016, Proceedings. Lecture Notes in Computer Science 9978, 2016, ISBN 978-3-319-49045-8 [contents] - 2015
- [j71]Aree Wiboonpongse, Jianxu Liu, Songsak Sriboonchitta, Thierry Denoeux:
Modeling dependence between error components of the stochastic frontier model using copula: Application to intercrop coffee production in Northern Thailand. Int. J. Approx. Reason. 65: 34-44 (2015) - [j70]Xun Wang, Shoumei Li, Thierry Denoeux:
Interval-Valued Linear Model. Int. J. Comput. Intell. Syst. 8(1): 114-127 (2015) - [j69]Lianmeng Jiao, Quan Pan, Thierry Denoeux, Yan Liang, Xiaoxue Feng:
Belief rule-based classification system: Extension of FRBCS in belief functions framework. Inf. Sci. 309: 26-49 (2015) - [j68]Thierry Denoeux, Orakanya Kanjanatarakul, Songsak Sriboonchitta:
EK-NNclus: A clustering procedure based on the evidential K-nearest neighbor rule. Knowl. Based Syst. 88: 57-69 (2015) - [j67]Chunfeng Lian, Su Ruan, Thierry Denoeux:
An evidential classifier based on feature selection and two-step classification strategy. Pattern Recognit. 48(7): 2318-2327 (2015) - [c75]Lianmeng Jiao, Thierry Denoeux, Quan Pan:
Evidential Editing K-Nearest Neighbor Classifier. ECSQARU 2015: 461-471 - [c74]Philippe Xu, Franck Davoine, Thierry Denoeux:
Evidential multinomial logistic regression for multiclass classifier calibration. FUSION 2015: 1106-1112 - [c73]Chunfeng Lian, Su Ruan, Thierry Denoeux, Pierre Vera:
Outcome prediction in tumour therapy based on Dempster-Shafer theory. ISBI 2015: 63-66 - [c72]Abdel-Djalil Ourabah, Benjamin Quost, Atef Gayed, Thierry Denoeux:
Estimating energy consumption of a PHEV using vehicle and on-board navigation data. Intelligent Vehicles Symposium 2015: 755-760 - [c71]Chunfeng Lian, Su Ruan, Thierry Denoeux, Hua Li, Pierre Vera:
Dempster-Shafer Theory Based Feature Selection with Sparse Constraint for Outcome Prediction in Cancer Therapy. MICCAI (3) 2015: 695-702 - [p3]