paper-with-me

Papers

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

2023-11-25 · 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

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 artificial neural networks that allow for recognizing meteor signals in the Mini-EUSO data with high accuracy in terms of a binary classification problem. We expect that similar architectures can be effectively used for signal recognition in other fluorescence telescopes, regardless of the nature of the signal. Due to their simplicity, the networks can be implemented in onboard electronics of future orbital or balloon experiments.

📄 PDF Abstract BibTeX arXiv:2311.14983

Code (0)

등록된 구현이 없습니다.

Tasks

Binary Classification

Similar Papers 제목 키워드 기반

Analysis of Fluorescence Telescope Data Using Machine Learning Methods

2025-01-04 · Mikhail Zotov, Pavel Zakharov

Fluorescence telescopes are among the key instruments used for studying ultra-high energy cosmic rays in all modern experiments. We use model data for a small ground-based telescope EUSO-TA to try some methods of machine…

A method for Cloud Mapping in the Field of View of the Infra-Red Camera during the EUSO-SPB1 flight

2019-09-12 · Alessandro Bruno, Anna Anzalone, Carlo Vigorito

EUSO-SPB1 was released on April 24th, 2017, from the NASA balloon launch site in Wanaka (New Zealand) and landed on the South Pacific Ocean on May 7th. The data collected by the instruments onboard the balloon were analy…

Image Enhancement

A Neural Network Approach for Selecting Track-like Events in Fluorescence Telescope Data

2022-12-07 · Mikhail Zotov, Denis Sokolinskii

In 2016-2017, TUS, the world's first experiment for testing the possibility of registering ultra-high energy cosmic rays (UHECRs) by their fluorescent radiation in the night atmosphere of Earth was carried out. Since 201…

NeuSort: An Automatic Adaptive Spike Sorting Approach with Neuromorphic Models

2023-04-20 · Hang Yu, Yu Qi, Gang Pan

Objective. Spike sorting, a critical step in neural data processing, aims to classify spiking events from single electrode recordings based on different waveforms. This study aims to develop a novel online spike sorter, …

Spike SortingTemplate Matching

Machine Learning Approach for Air Shower Recognition in EUSO-SPB Data

2019-09-09 · Michal Vrábel, Ján Genči, Pavol Bobik, Francesca Bisconti

The main goal of The Extreme Universe Space Observatory on a Super Pressure Balloon (EUSO-SPB1) was to observe from above extensive air showers caused by ultra-high energy cosmic rays. EUSO-SPB1 uses a fluorescence detec…

BIG-bench Machine Learning