| Application of the deep convolutional neural network to the forecast of solar flare occurrence using full-disk solar magnetograms E Park, YJ Moon, S Shin, K Yi, D Lim, H Lee, G Shin The Astrophysical Journal 869 (2), 91, 2018 | 99 | 2018 |
| Solar farside magnetograms from deep learning analysis of STEREO/EUVI data T Kim, E Park, H Lee, YJ Moon, SH Bae, D Lim, S Jang, L Kim, IH Cho, ... Nature Astronomy 3 (5), 397-400, 2019 | 94 | 2019 |
| One‐day forecasting of global TEC using a novel deep learning model S Lee, EY Ji, YJ Moon, E Park Space Weather 19 (1), 2020SW002600, 2021 | 41 | 2021 |
| Visual explanation of a deep learning solar flare forecast model and its relationship to physical parameters K Yi, YJ Moon, D Lim, E Park, H Lee The Astrophysical Journal 910 (1), 8, 2021 | 36 | 2021 |
| Nighttime reflectance generation in the visible band of satellites K Kim, JH Kim, YJ Moon, E Park, G Shin, T Kim, Y Kim, S Hong Remote Sensing 11 (18), 2087, 2019 | 29 | 2019 |
| Generation of solar UV and EUV images from SDO/HMI magnetograms by deep learning E Park, YJ Moon, JY Lee, H Lee, D Lim, G Shin, T Kim The Astrophysical Journal Letters 884 (1), L23, 2019 | 27 | 2019 |
| Solar coronal magnetic field extrapolation from synchronic data with AI-generated farside HJ Jeong, YJ Moon, E Park, H Lee The Astrophysical Journal Letters 903 (2), L25, 2020 | 26 | 2020 |
| Improvement of IRI global TEC maps by deep learning based on conditional Generative Adversarial Networks EY Ji, YJ Moon, E Park Space Weather 18 (5), e2019SW002411, 2020 | 25 | 2020 |
| Generation of high-resolution solar pseudo-magnetograms from Ca ii K images by deep learning G Shin, YJ Moon, E Park, HJ Jeong, H Lee, SH Bae The Astrophysical Journal Letters 895 (1), L16, 2020 | 24 | 2020 |
| Super-resolution of SDO/HMI magnetograms using novel deep learning methods S Rahman, YJ Moon, E Park, A Siddique, IH Cho, D Lim The Astrophysical Journal Letters 897 (2), L32, 2020 | 16 | 2020 |
| De-noising SDO/HMI solar magnetograms by image translation method based on deep learning E Park, YJ Moon, D Lim, H Lee The Astrophysical Journal Letters 891 (1), L4, 2020 | 15 | 2020 |
| Generation of He i 1083 nm images from SDO AIA images by deep learning J Son, J Cha, YJ Moon, H Lee, E Park, G Shin, HJ Jeong The Astrophysical Journal 920 (2), 101, 2021 | 14 | 2021 |
| Generation of modern satellite data from Galileo sunspot drawings in 1612 by deep learning H Lee, E Park, YJ Moon The Astrophysical Journal 907 (2), 118, 2021 | 9 | 2021 |
| Ensemble forecasting of major solar flares with short-, mid-, and long-term active region properties D Lim, YJ Moon, E Park, J Park, K Lee, JY Lee, S Jang The Astrophysical Journal 885 (1), 35, 2019 | 9 | 2019 |
| Improved AI-generated solar farside magnetograms by STEREO and SDO data sets and their release HJ Jeong, YJ Moon, E Park, H Lee, JH Baek The Astrophysical Journal Supplement Series 262 (2), 50, 2022 | 8 | 2022 |
| Forecast of daily major flare probability using relationships between vector magnetic properties and flaring rates D Lim, YJ Moon, J Park, E Park, K Lee, JY Lee, S Jang arXiv preprint arXiv:1907.11373, 2019 | 7 | 2019 |
| Fast reconstruction of 3D density distribution around the sun based on the MAS by deep learning S Rahman, S Shin, HJ Jeong, A Siddique, YJ Moon, E Park, J Kang, ... The Astrophysical Journal 948 (1), 21, 2023 | 6 | 2023 |
| Generation of Solar Coronal White-light Images from SDO/AIA EUV Images by Deep Learning B Lawrance, H Lee, E Park, IH Cho, YJ Moon, JY Lee, A Shanmugaraju, ... The Astrophysical Journal 937 (2), 111, 2022 | 5 | 2022 |
| Three-dimensional oscillations of 21 halo coronal mass ejections using multi-spacecraft data H Lee, YJ Moon, VM Nakariakov, H Na, IH Cho, E Park The Astrophysical Journal 868 (1), 18, 2018 | 4 | 2018 |
| Observational test of empirical magnetopause location models using geosynchronous satellite data E Park, YJ Moon, K Lee Journal of Geophysical Research: Space Physics 121 (11), 10,994-11,006, 2016 | 4 | 2016 |
