10 citations · 27 across the 7 of their papers we have counts for
7 papers
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…
In-Bed Pose Estimation: A Review
Ziya Ata Yazıcı, Sara Colantonio, Hazım Kemal Ekenel
Human pose estimation, the process of identifying joint positions in a person's body from images or videos, represents a widely utilized technology across diverse fields, including…
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…
The role of causality in explainable artificial intelligence
Gianluca Carloni, Andrea Berti, Sara Colantonio
Causality and eXplainable Artificial Intelligence (XAI) have developed as separate fields in computer science, even though the underlying concepts of causation and explanation shar…
Alzheimer Disease Detection from Raman Spectroscopy of the Cerebrospinal Fluid via Topological Machine Learning
Francesco Conti, Martina Banchelli, Valentina Bessi +10
The cerebrospinal fluid (CSF) of 19 subjects who received a clinical diagnosis of Alzheimer's disease (AD) as well as of 5 pathological controls have been collected and analysed by…
Reproducibility of Machine Learning: Terminology, Recommendations and Open Issues
Riccardo Albertoni, Sara Colantonio, Piotr Skrzypczyński +1
Reproducibility is one of the core dimensions that concur to deliver Trustworthy Artificial Intelligence. Broadly speaking, reproducibility can be defined as the possibility to rep…