Using deep learning to identify and classify sunspots in magnetograms
Some of the solar activities, such as solar flares, release large amounts of radiation and energy that impact on Earth's life and technological systems. These flares usually come from sunspots, which derive from solar magnetic activities. Currently, some solar data allow predicting when a solar...
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| Main Authors: | , |
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| Format: | Online |
| Language: | Portuguese |
| Published: |
Universidade Estadual de Campinas
2019
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| Subjects: | |
| Online Access: | https://econtents.sbu.unicamp.br/eventos/index.php/pibic/article/view/2309 |
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| Summary: | Some of the solar activities, such as solar flares, release large amounts of radiation and energy that impact on Earth's life and technological systems. These flares usually come from sunspots, which derive from solar magnetic activities. Currently, some solar data allow predicting when a solar flare will occur. This paper reports the use of the Deep Learning technique to identify and classify sunspots using solar magnetograms automatically. Our results show an accuracy greater than 80%. |
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| ISSN: | 2596-1969 |
