Neural Network Based Approach to Recognition of Meteor Tracks in the Mini-EUSO Telescope Data

Neural Network Based Approach to Recognition of Meteor Tracks in the Mini-EUSO Telescope Data

Mini-EUSO is a wide-angle fluorescence telescope that registers ultraviolet (UV) radiation in the nocturnal atmosphere of Earth from the International Space Station. Meteors are among multiple phenomena that manifest themselves not only in the visible range but also in the UV. We present two simple...

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Bibliographic Details
Main Authors: Mikhail Zotov, Dmitry Anzhiganov, Aleksandr Kryazhenkov, Dario Barghini, Matteo Battisti, Alexander Belov, Mario Bertaina, Marta Bianciotto, Francesca Bisconti, Carl Blaksley, Sylvie Blin, Giorgio Cambiè, Francesca Capel, Marco Casolino, Toshikazu Ebisuzaki, Johannes Eser, Francesco Fenu, Massimo Alberto Franceschi, Alessio Golzio, Philippe Gorodetzky, Fumiyoshi Kajino, Hiroshi Kasuga, Pavel Klimov, Massimiliano Manfrin, Laura Marcelli, Hiroko Miyamoto, Alexey Murashov, Tommaso Napolitano, Hiroshi Ohmori, Angela Olinto, Etienne Parizot, Piergiorgio Picozza, Lech Wiktor Piotrowski, Zbigniew Plebaniak, Guillaume Prévôt, Enzo Reali, Marco Ricci, Giulia Romoli, Naoto Sakaki, Kenji Shinozaki, Christophe De La Taille, Yoshiyuki Takizawa, Michal Vrábel, Lawrence Wiencke
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Algorithms
Subjects:
machine learning
neural network
pattern recognition
meteor
fluorescence telescope
orbital experiment
Online Access:https://www.mdpi.com/1999-4893/16/9/448

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https://www.mdpi.com/1999-4893/16/9/448

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