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09/12/2023
Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation
Single-modality medical images generally do not contain enough informati...
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08/01/2022
An Evidential Neural Network Model for Regression Based on Random Fuzzy Numbers
We introduce a distance-based neural network model for regression, in wh...
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06/23/2022
Evidence fusion with contextual discounting for multi-modality medical image segmentation
As information sources are usually imperfect, it is necessary to take in...
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02/16/2022
Reasoning with fuzzy and uncertain evidence using epistemic random fuzzy sets: general framework and practical models
We introduce a general theory of epistemic random fuzzy sets for reasoni...
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01/31/2022
Lymphoma segmentation from 3D PET-CT images using a deep evidential network
An automatic evidential segmentation method based on Dempster-Shafer the...
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08/25/2021
Clustering acoustic emission data streams with sequentially appearing clusters using mixture models
The interpretation of unlabeled acoustic emission (AE) data classically ...
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08/23/2021
Fusion of evidential CNN classifiers for image classification
We propose an information-fusion approach based on belief functions to c...
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08/11/2021
Deep PET/CT fusion with Dempster-Shafer theory for lymphoma segmentation
Lymphoma detection and segmentation from whole-body Positron Emission To...
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04/27/2021
Evidential segmentation of 3D PET/CT images
PET and CT are two modalities widely used in medical image analysis. Acc...
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01/29/2021
Belief function-based semi-supervised learning for brain tumor segmentation
Precise segmentation of a lesion area is important for optimizing its tr...
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01/18/2021
Covid-19 classification with deep neural network and belief functions
Computed tomography (CT) image provides useful information for radiologi...
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10/03/2020
EGMM: an Evidential Version of the Gaussian Mixture Model for Clustering
The Gaussian mixture model (GMM) provides a convenient yet principled fr...
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09/27/2020
NN-EVCLUS: Neural Network-based Evidential Clustering
Evidential clustering is an approach to clustering based on the use of D...
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04/24/2020
Belief functions induced by random fuzzy sets: Application to statistical inference
We revisit Zadeh's notion of "evidence of the second kind" and show that...
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12/13/2019
From Shallow to Deep Interactions Between Knowledge Representation, Reasoning and Machine Learning (Kay R. Amel group)
This paper proposes a tentative and original survey of meeting points be...
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12/13/2019
An Interval-Valued Utility Theory for Decision Making with Dempster-Shafer Belief Functions
The main goal of this paper is to describe an axiomatic utility theory f...
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12/12/2019
Calibrated model-based evidential clustering using bootstrapping
Evidential clustering is an approach to clustering in which cluster-memb...
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08/16/2018
Decision-Making with Belief Functions: a Review
Approaches to decision-making under uncertainty in the belief function f...
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07/05/2018