Parmiggiani, N. https://orcid.org/0000-0002-4535-5329
Bulgarelli, A. https://orcid.org/0000-0001-6347-0649
Ursi, A. https://orcid.org/0000-0002-7253-9721
Macaluso, A. https://orcid.org/0000-0002-1348-250X
Di Piano, A. https://orcid.org/0000-0002-9894-7491
Fioretti, V. https://orcid.org/0000-0002-6082-5384
Aboudan, A. https://orcid.org/0000-0002-8290-2184
Baroncelli, L. https://orcid.org/0000-0002-9215-4992
Addis, A. https://orcid.org/0000-0002-0886-8045
Tavani, M. https://orcid.org/0000-0003-2893-1459
Pittori, C. https://orcid.org/0000-0001-6661-9779
Funding for this research was provided by:
Agenzia Spaziale Italiana (I/028/12/6 and I/028/12.7-2022)
Article Title: A Deep-learning Anomaly-detection Method to Identify Gamma-Ray Bursts in the Ratemeters of the AGILE Anticoincidence System
Journal Title: The Astrophysical Journal
Article Type: paper
Copyright Information: © 2023. The Author(s). Published by the American Astronomical Society.
Publication dates
Date Received: 2022-07-10
Date Accepted: 2023-02-06
Online publication date: 2023-03-13