Deep Learning Method for Martian Atmosphere Reconstruction. - Davide Amato; Jay W. McMahon (J. Aerosp. Inf. Syst., 2021)

Towards the Future Generation of Railway Localization and Signaling Exploiting sub-meter RTK GNSS. - Carla Amatetti; Tommaso Polonelli; Enea Masina; Charles Moatti; Denis Mikhaylov; Davide Amato; Alessandro Vanelli-Coralli; Michele Magno; Luca Benini (SAS, 2022)

Incremental Correction in Dynamic Systems Modelled with Neural Networks for Constraint Satisfaction. - Namhoon Cho; Hyo-Sang Shin; Antonios Tsourdos; Davide Amato (CoRR, 2022)

A 2.4 GHz Modular Antenna System for Train Integrity and Localization Purposes. - Giacomo Paolini; Enrico Fazzini; Simone Trovarello; Davide Amato; Diego Masotti; Alessandra Costanzo (RFID-TA, 2023)

Density Estimation for Entry Guidance Problems using Deep Learning. - Jens A. Rataczak; Davide Amato; Jay W. McMahon (CoRR, 2023)

Toward the Future Generation of Railway Localization Exploiting RTK and GNSS. - Denis Mikhaylov; Carla Amatetti; Tommaso Polonelli; Enea Masina; Riccardo Campana; Kai Berszin; Charles Moatti; Davide Amato; Alessandro Vanelli-Coralli; Michele Magno; Luca Benini (IEEE Trans. Instrum. Meas., 2023)

Towards the Future Generation of Railway Localization Exploiting RTK and GNSS. - Denis Mikhaylov; Carla Amatetti; Tommaso Polonelli; Enea Masina; Riccardo Campana; Kai Berszin; Davide Amato; Alessandro Vanelli-Coralli; Michele Magno; Luca Benini (Zenodo, 2023)

Enhancing LoRaWAN-Based Railway Signalling Systems for Secondary Lines: A Probabilistic Analysis of Multi-Hop Localization. - Danila Ferretti; Davide Amato; Roberto Verdone (VTC Fall, 2024)