39 citations · 56 across the 9 of their papers we have counts for
5 papers · 1 filter
Connectivity-Inspired Network for Context-Aware Recognition
Gianluca Carloni, Sara Colantonio
The aim of this paper is threefold. We inform the AI practitioner about the human visual system with an extensive literature review; we propose a novel biologically motivated neura…
Boosting Few-Shot Learning with Disentangled Self-Supervised Learning and Meta-Learning for Medical Image Classification
Eva Pachetti, Sotirios A. Tsaftaris, Sara Colantonio
Background and objective: Employing deep learning models in critical domains such as medical imaging poses challenges associated with the limited availability of training data. We…
Causality-Driven One-Shot Learning for Prostate Cancer Grading from MRI
Gianluca Carloni, Eva Pachetti, Sara Colantonio
In this paper, we present a novel method to automatically classify medical images that learns and leverages weak causal signals in the image. Our framework consists of a convolutio…
A Systematic Review of Few-Shot Learning in Medical Imaging
Eva Pachetti, Sara Colantonio
The lack of annotated medical images limits the performance of deep learning models, which usually need large-scale labelled datasets. Few-shot learning techniques can reduce data…
Exploiting Causality Signals in Medical Images: A Pilot Study with Empirical Results
Gianluca Carloni, Sara Colantonio
We present a novel technique to discover and exploit weak causal signals directly from images via neural networks for classification purposes. This way, we model how the presence o…