Coronal Mass Ejections (CMEs) are massive releases of plasma from the solar corona. When the charged material is ejected towards the Earth, it can cause geomagnetic storms and severely damage electronic equipment and power grids. Early detection of CMEs is therefore crucial for damage containment. In this paper, we study detection of CMEs from sequential images of the solar corona acquired by a satellite. A low-complexity deep neural network is trained to process the raw images, ideally directly on the satellite, in order to provide early alerts.

Detection of Solar Coronal Mass Ejections from Raw Images with Deep Convolutional Neural Networks / Valsesia, D.; Grippi, A.; Magli, E.; Susino, R.; Telloni, D.; Nicolini, G.; Casti, M.; Mulone, A. F.; Messineo, R.. - (2020), pp. 2272-2275. ((Intervento presentato al convegno 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 tenutosi a usa nel 2020 [10.1109/IGARSS39084.2020.9323169].

Detection of Solar Coronal Mass Ejections from Raw Images with Deep Convolutional Neural Networks

Valsesia D.;Magli E.;
2020

Abstract

Coronal Mass Ejections (CMEs) are massive releases of plasma from the solar corona. When the charged material is ejected towards the Earth, it can cause geomagnetic storms and severely damage electronic equipment and power grids. Early detection of CMEs is therefore crucial for damage containment. In this paper, we study detection of CMEs from sequential images of the solar corona acquired by a satellite. A low-complexity deep neural network is trained to process the raw images, ideally directly on the satellite, in order to provide early alerts.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2880003