440 citations · 787 across the 29 of their papers we have counts for
9 papers · 1 filter
A Federated Learning Platform as a Service for Advancing Stroke Management in European Clinical Centers
Diogo Reis Santos, Albert Sund Aillet, Antonio Boiano +10
The rapid evolution of artificial intelligence (AI) technologies holds transformative potential for the healthcare sector. In critical situations requiring immediate decision-makin…
On the impact of the antenna radiation patterns in passive radio sensing
Federica Fieramosca, Vittorio Rampa, Stefano Savazzi +1
Electromagnetic (EM) body models based on the scalar diffraction theory allow to predict the impact of subject motions on the radio propagation channel without requiring a time-con…
Full-wave EM simulation analysis of human body blockage by dense 2D antenna arrays
Federica Fieramosca, Vittorio Rampa, Michele D'Amico +1
Recently, proposals of human-sensing-based services for cellular and local area networks have brought indoor localization to the attention of several research groups. In response t…
Physics-informed generative neural networks for RF propagation prediction with application to indoor body perception
Federica Fieramosca, Vittorio Rampa, Michele D'Amico +1
Electromagnetic (EM) body models designed to predict Radio-Frequency (RF) propagation are time-consuming methods which prevent their adoption in strict real-time computational imag…
Compressed Bayesian Federated Learning for Reliable Passive Radio Sensing in Industrial IoT
Luca Barbieri, Stefano Savazzi, Monica Nicoli
Bayesian Federated Learning (FL) has been recently introduced to provide well-calibrated Machine Learning (ML) models quantifying the uncertainty of their predictions. Despite thei…
Cooperation and Federation in Distributed Radar Point Cloud Processing
S. Savazzi, V. Rampa, S. Kianoush +2
The paper considers the problem of human-scale RF sensing utilizing a network of resource-constrained MIMO radars with low range-azimuth resolution. The radars operate in the mmWav…
An EM Body Model for Device-Free Localization with Multiple Antenna Receivers: A First Study
Vittorio Rampa, Federica Fieramosca, Stefano Savazzi +1
Device-Free Localization (DFL) employs passive radio techniques capable to detect and locate people without imposing them to wear any electronic device. By exploiting the Integrate…
A Secure and Trustworthy Network Architecture for Federated Learning Healthcare Applications
Antonio Boiano, Marco Di Gennaro, Luca Barbieri +7
Federated Learning (FL) has emerged as a promising approach for privacy-preserving machine learning, particularly in sensitive domains such as healthcare. In this context, the TRUS…
On the Impact of Data Heterogeneity in Federated Learning Environments with Application to Healthcare Networks
Usevalad Milasheuski, Luca Barbieri, Bernardo Camajori Tedeschini +2
Federated Learning (FL) allows multiple privacy-sensitive applications to leverage their dataset for a global model construction without any disclosure of the information. One of t…