Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Antonio Montanaro"'
Autor:
Leonardo Olivi, Antonio Montanaro, Mario Edoardo Bertaina, Antonio Giulio Coretti, Dario Barghini, Matteo Battisti, Alexander Belov, Marta Bianciotto, Francesca Bisconti, Carl Blaksley, Sylvie Blin, Karl Bolmgren, Giorgio Cambie, Francesca Capel, Marco Casolino, Igor Churilo, Marino Crisconio, Christophe De La Taille, Toshikazu Ebisuzaki, Johannes Eser, Francesco Fenu, George Filippatos, Massimo Alberto Franceschi, Christer Fuglesang, Alessio Golzio, Philippe Gorodetzky, Fumiyoshi Kajino, Hiroshi Kasuga, Pavel Klimov, Viktoria Kungel, Vladimir Kuznetsov, Massimiliano Manfrin, Laura Marcelli, Gabriele Mascetti, Wlodzimierz Marszal, Marco Mignone, Hiroko Miyamoto, Alexey Murashov, Tommaso Napolitano, Hitoshi Ohmori, Angela Olinto, Etienne Parizot, Piergiorgio Picozza, Lech Wiktor Piotrowski, Zbigniew Plebaniak, Guillaume Prevot, Enzo Reali, Marco Ricci, Giulia Romoli, Naoto Sakaki, Sergei Sharakin, Kenji Shinozaki, Jacek Szabelski, Yoshiyuki Takizawa, Valerio Vagelli, Giovanni Valentini, Michal Vrabel, Lawrence Wiencke, Mikhail Zotov
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 10432-10453 (2024)
In this article, we present cutting-edge machine learning-based techniques for the detection and reconstruction of meteors and space debris in the Mini-EUSO experiment, a detector installed on board of the International Space Station, and pointing to
Externí odkaz:
https://doaj.org/article/3e7af6b6f04241f1b1353d702b1b2b90
Autor:
Dario Barghini, Mario Bertaina, Alberto Cellino, Francesco Fenu, Silvia Ferrarese, Alessio Golzio, Oliver I. Ruiz-Hernandez, Pavel Klimov, Antonio Montanaro, Anthony Salsi, Sergei Sharakin, Ksenia Sigaeva, Mikhail Zotov
Publikováno v:
Advances in Space Research. 70:2734-2749
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Semi-supervised learning techniques are gaining popularity due to their capability of building models that are effective, even when scarce amounts of labeled data are available. In this paper, we present a framework and specific tasks for self-superv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b7d220d1b23f48e58ed7f1b80008e31d
http://arxiv.org/abs/2108.09075
http://arxiv.org/abs/2108.09075
Autor:
S. A. Sharakin, M. E. Bertaina, Antonio Montanaro, Silvia Ferrarese, Fracesco Isgró, Rosella Caruso, Pavel Klimov, Alberto Cellino, Antonella Castellina, Mikhail Zotov, Francesco Fenu, A. Anzalone, Kenji Shinozaki
Publikováno v:
Scopus-Elsevier
Nuclearites are a hypothetical massive strange quark matter. They are supposed to be gravitationally trapped in Our Galaxy. Their absolute velocity is considered to be similar to that of the galactic rotation near the Sun. When the nucleartite traver