Generation of Solar UV and EUV Images from SDO/HMI Magnetograms by Deep Learning

In this Letter, we apply deep-learning methods to the image-to-image translation from solar magnetograms to solar ultraviolet (UV) and extreme UV (EUV) images. For this, We consider two convolutional neural network models with different loss functions, one (Model A) is with L1 loss (L1), and the oth...

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Veröffentlicht in:	Astrophysical journal. Letters 2019-10, Vol.884 (1), p.L23
Hauptverfasser:	Park, Eunsu, Moon, Yong-Jae, Lee, Jin-Yi, Kim, Rok-Soon, Lee, Harim, Lim, Daye, Shin, Gyungin, Kim, Taeyoung
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Atmospheric models Correlation coefficient Correlation coefficients Deep learning Image contrast Line of sight methods: data analysis Neural networks Pixels Solar activity Solar observatories Sun: atmosphere techniques: image processing Ultraviolet radiation
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