212 citations · 850 across the 18 of their papers we have counts for
7 papers · 1 filter
Fusion of evidential CNN classifiers for image classification
Zheng Tong, Philippe Xu, Thierry Denoeux
We propose an information-fusion approach based on belief functions to combine convolutional neural networks. In this approach, several pre-trained DS-based CNN architectures extra…
Deep PET/CT fusion with Dempster-Shafer theory for lymphoma segmentation
Ling Huang, Thierry Denoeux, David Tonnelet +2
Lymphoma detection and segmentation from whole-body Positron Emission Tomography/Computed Tomography (PET/CT) volumes are crucial for surgical indication and radiotherapy. Designin…
Clustering acoustic emission data streams with sequentially appearing clusters using mixture models
Emmanuel Ramasso, Thierry Denoeux, Gael Chevallier
The interpretation of unlabeled acoustic emission (AE) data classically relies on general-purpose clustering methods. While several external criteria have been used in the past to…
Evidential segmentation of 3D PET/CT images
Ling Huang, Su Ruan, Pierre Decazes +1
PET and CT are two modalities widely used in medical image analysis. Accurately detecting and segmenting lymphomas from these two imaging modalities are critical tasks for cancer s…
An evidential classifier based on Dempster-Shafer theory and deep learning
Zheng Tong, Philippe Xu, Thierry Denœux
We propose a new classifier based on Dempster-Shafer (DS) theory and a convolutional neural network (CNN) architecture for set-valued classification. In this classifier, called the…
Belief function-based semi-supervised learning for brain tumor segmentation
Ling Huang, Su Ruan, Thierry Denoeux
Precise segmentation of a lesion area is important for optimizing its treatment. Deep learning makes it possible to detect and segment a lesion field using annotated data. However,…
Covid-19 classification with deep neural network and belief functions
Ling Huang, Su Ruan, Thierry Denoeux
Computed tomography (CT) image provides useful information for radiologists to diagnose Covid-19. However, visual analysis of CT scans is time-consuming. Thus, it is necessary to d…