Using deep learning to identify and classify sunspots in magnetograms
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Palavras-chave

Solar flares
Deep learning
Object detection

Como Citar

OLIVEIRA, Letícia de; GRADVOHL, Andre. Using deep learning to identify and classify sunspots in magnetograms. Revista dos Trabalhos de Iniciação Científica da UNICAMP, Campinas, SP, n. 27, p. 1–1, 2019. DOI: 10.20396/revpibic2720192309. Disponível em: https://econtents.bc.unicamp.br/eventos/index.php/pibic/article/view/2309. Acesso em: 20 abr. 2024.

Resumo

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%.

https://doi.org/10.20396/revpibic2720192309
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Referências

GRADVOHL, A. L. S&FERNANDES,M.E.R.(2017).Samplesofsolar flares classes, active regions and time of occurrence (Version 0.1) [Dataset]. Available at: http://doi.org/10.5281/ zenodo.1048995. Access on June 29, 2019.
NVIDIA DIGITS. Interactive Deep Learning GPU Training System. NVIDIA Corporation, [2016]. Available at: https://developer.nvidia.com/ digits. Access on June 29, 2019. 

Todos os trabalhos são de acesso livre, sendo que a detenção dos direitos concedidos aos trabalhos são de propriedade da Revista dos Trabalhos de Iniciação Científica da UNICAMP.

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