7 papers
SAR Vessel Detection and Gross Tonnage Estimation from Heterogeneous Datasets for Dark Vessel Identification
Davide Paltrinieri, Andrea Diecidue, Roberto Basla +3
Detecting vessels engaging in illegal activities is of paramount importance for maritime security. One of the major goals is to detect dark vessels, ships that disable their transp…
The silence of the weights: a structural pruning strategy for attention-based audio signal architectures with second order metrics
Andrea Diecidue, Carlo Alberto Barbano, Piero Fraternali +2
Transformer-based models have become the state of the art across multiple domains, from natural language processing to machine listening, thanks to the attention mechanisms. Howeve…
DeepRed: an architecture for redshift estimation
Alessandro Meroni, Nicolò Oreste Pinciroli Vago, Piero Fraternali
Estimating redshift is a central task in astrophysics, but its measurement is costly and time-consuming. In addition, current image-based methods are often validated on homogeneous…
A Graph-based RAG for Energy Efficiency Question Answering
Riccardo Campi, Nicolò Oreste Pinciroli Vago, Mathyas Giudici +3
In this work, we investigate the use of Large Language Models (LLMs) within a graph-based Retrieval Augmented Generation (RAG) architecture for Energy Efficiency (EE) Question Answ…
A Deep Learning Pipeline for Solid Waste Detection in Remote Sensing Images
Federico Gibellini, Piero Fraternali, Giacomo Boracchi +4
Improper solid waste management represents both a serious threat to ecosystem health and a significant source of revenues for criminal organizations perpetrating environmental crim…
The hunt for new pulsating ultraluminous X-ray sources: a clustering approach
Nicolò Oreste Pinciroli Vago, Roberta Amato, Matteo Imbrogno +5
The discovery of fast and variable coherent signals in a handful of ultraluminous X-ray sources (ULXs) testifies to the presence of super-Eddington accreting neutron stars, and dra…