42 citations · 79 across the 9 of their papers we have counts for
9 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…
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…
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…
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…
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…
Time Series Analysis in Compressor-Based Machines: A Survey
Francesca Forbicini, Nicolò Oreste Pinciroli Vago, Piero Fraternali
In both industrial and residential contexts, compressor-based machines, such as refrigerators, HVAC systems, heat pumps and chillers, are essential to fulfil production and consume…
Predicting machine failures from multivariate time series: an industrial case study
Nicolò Oreste Pinciroli Vago, Francesca Forbicini, Piero Fraternali
Non-neural Machine Learning (ML) and Deep Learning (DL) models are often used to predict system failures in the context of industrial maintenance. However, only a few researches jo…
Solid Waste Detection, Monitoring and Mapping in Remote Sensing Images: A Survey
Piero Fraternali, Luca Morandini, Sergio Luis Herrera González
The detection and characterization of illegal solid waste disposal sites are essential for environmental protection, particularly for mitigating pollution and health hazards. Impro…