92 citations · 193 across the 8 of their papers we have counts for
3 papers · 1 filter
GraphXCOVID: Explainable Deep Graph Diffusion Pseudo-Labelling for Identifying COVID-19 on Chest X-rays
Angelica I Aviles-Rivero, Philip Sellars, Carola-Bibiane Schönlieb +1
Can one learn to diagnose COVID-19 under extreme minimal supervision? Since the outbreak of the novel COVID-19 there has been a rush for developing Artificial Intelligence techniqu…
The GraphNet Zoo: An All-in-One Graph Based Deep Semi-Supervised Framework for Medical Image Classification
Marianne de Vriendt, Philip Sellars, Angelica I Aviles-Rivero
We consider the problem of classifying a medical image dataset when we have a limited amounts of labels. This is very common yet challenging setting as labelled data is expensive,…
CycleCluster: Modernising Clustering Regularisation for Deep Semi-Supervised Classification
Philip Sellars, Angelica Aviles-Rivero, Carola Bibiane Schönlieb
Given the potential difficulties in obtaining large quantities of labelled data, many works have explored the use of deep semi-supervised learning, which uses both labelled and unl…