429 citations · 664 across the 34 of their papers we have counts for
3 papers · 1 filter
A transductive few-shot learning approach for classification of digital histopathological slides from liver cancer
Aymen Sadraoui, Ségolène Martin, Eliott Barbot +4
This paper presents a new approach for classifying 2D histopathology patches using few-shot learning. The method is designed to tackle a significant challenge in histopathology, wh…
Negative Evidence Matters in Interpretable Histology Image Classification
Soufiane Belharbi, Marco Pedersoli, Ismail Ben Ayed +2
Using only global image-class labels, weakly-supervised learning methods, such as class activation mapping, allow training CNNs to jointly classify an image, and locate regions of…
Segmentation with mixed supervision: Confidence maximization helps knowledge distillation
Bingyuan Liu, Christian Desrosiers, Ismail Ben Ayed +1
Despite achieving promising results in a breadth of medical image segmentation tasks, deep neural networks require large training datasets with pixel-wise annotations. Obtaining th…