4 papers
SeeingSounds: Learning Audio-to-Visual Alignment via Text
Simone Carnemolla, Matteo Pennisi, Chiara Russo +3
We introduce SeeingSounds, a lightweight and modular framework for audio-to-image generation that leverages the interplay between audio, language, and vision-without requiring any…
Self-supervised learning for radio-astronomy source classification: a benchmark
Thomas Cecconello, Simone Riggi, Ugo Becciani +5
The upcoming Square Kilometer Array (SKA) telescope marks a significant step forward in radio astronomy, presenting new opportunities and challenges for data analysis. Traditional…
Evidential Federated Learning for Skin Lesion Image Classification
Rutger Hendrix, Federica Proietto Salanitri, Concetto Spampinato +2
We introduce FedEvPrompt, a federated learning approach that integrates principles of evidential deep learning, prompt tuning, and knowledge distillation for distributed skin lesio…
FedRewind: Rewinding Continual Model Exchange for Decentralized Federated Learning
Luca Palazzo, Matteo Pennisi, Federica Proietto Salanitri +3
In this paper, we present FedRewind, a novel approach to decentralized federated learning that leverages model exchange among nodes to address the issue of data distribution shift.…