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Cited by in F6Publishing
For: Park E, Moon Y, Shin S, Yi K, Lim D, Lee H, Shin G. Application of the Deep Convolutional Neural Network to the Forecast of Solar Flare Occurrence Using Full-disk Solar Magnetograms. ApJ 2018;869:91. [DOI: 10.3847/1538-4357/aaed40] [Cited by in Crossref: 27] [Cited by in F6Publishing: 22] [Article Influence: 6.8] [Reference Citation Analysis]
Number Citing Articles
1 Pandey C, Ji A, Angryk RA, Georgoulis MK, Aydin B. Towards coupling full-disk and active region-based flare prediction for operational space weather forecasting. Front Astron Space Sci 2022;9:897301. [DOI: 10.3389/fspas.2022.897301] [Reference Citation Analysis]
2 Deshmukh V, Flyer N, van der Sande K, Berger T. Decreasing False-alarm Rates in CNN-based Solar Flare Prediction Using SDO/HMI Data. ApJS 2022;260:9. [DOI: 10.3847/1538-4365/ac5b0c] [Reference Citation Analysis]
3 Erdélyi R, Korsós MB, Huang X, Yang Y, Pizzey D, Wrathmall SA, Hughes IG, Dyer MJ, Dhillon VS, Belucz B, Brajša R, Chatterjee P, Cheng X, Deng Y, Domínguez SV, Joya R, Gömöry P, Gyenge NG, Hanslmeier A, Kucera A, Kuridze D, Li F, Liu Z, Xu L, Mathioudakis M, Matthews S, Mcateer JR, Pevtsov AA, Pötzi W, Romano P, Shen J, Temesváry J, Tlatov AG, Triana C, Utz D, Veronig AM, Wang Y, Yan Y, Zaqarashvili T, Zuccarello F. The Solar Activity Monitor Network – SAMNet. J Space Weather Space Clim 2022;12:2. [DOI: 10.1051/swsc/2021025] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
4 Landa V, Reuveni Y. Low-dimensional Convolutional Neural Network for Solar Flares GOES Time-series Classification. ApJS 2022;258:12. [DOI: 10.3847/1538-4365/ac37bc] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
5 Nogay HS, Akinci TC, Yilmaz M. Detection of invisible cracks in ceramic materials using by pre-trained deep convolutional neural network. Neural Comput & Applic 2022;34:1423-32. [DOI: 10.1007/s00521-021-06652-w] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
6 Deng Z, Wang F, Deng H, Tan L, Deng L, Feng S. Fine-grained Solar Flare Forecasting Based on the Hybrid Convolutional Neural Networks*. ApJ 2021;922:232. [DOI: 10.3847/1538-4357/ac2b2b] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Nishizuka N, Kubo Y, Sugiura K, Den M, Ishii M. Operational solar flare prediction model using Deep Flare Net. Earth Planets Space 2021;73. [DOI: 10.1186/s40623-021-01381-9] [Cited by in Crossref: 8] [Cited by in F6Publishing: 5] [Article Influence: 8.0] [Reference Citation Analysis]
8 Tang R, Liao W, Chen Z, Zeng X, Wang J, Luo B, Chen Y, Cui Y, Zhou M, Deng X, Li H, Yuan K, Hong S, Wu Z. Solar Flare Prediction Based on the Fusion of Multiple Deep-learning Models. ApJS 2021;257:50. [DOI: 10.3847/1538-4365/ac249e] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
9 Baek J, Kim S, Choi S, Park J, Kim J, Jo W, Kim D. Solar Event Detection Using Deep-Learning-Based Object Detection Methods. Sol Phys 2021;296. [DOI: 10.1007/s11207-021-01902-5] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
10 Zheng Y, Li X, Si Y, Qin W, Tian H. Hybrid deep convolutional neural network with one-versus-one approach for solar flare prediction. Monthly Notices of the Royal Astronomical Society 2021;507:3519-39. [DOI: 10.1093/mnras/stab2132] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
11 Abed AK, Qahwaji R, Abed A. The automated prediction of solar flares from SDO images using deep learning. Advances in Space Research 2021;67:2544-57. [DOI: 10.1016/j.asr.2021.01.042] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 6.0] [Reference Citation Analysis]
12 Yi K, Moon Y, Lim D, Park E, Lee H. Visual Explanation of a Deep Learning Solar Flare Forecast Model and Its Relationship to Physical Parameters. ApJ 2021;910:8. [DOI: 10.3847/1538-4357/abdebe] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
13 Benvenuto F, Campi C, Massone AM, Piana M. Machine Learning as a Flaring Storm Warning Machine: Was a Warning Machine for the 2017 September Solar Flaring Storm Possible? ApJ 2020;904:L7. [DOI: 10.3847/2041-8213/abc5b7] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 2.5] [Reference Citation Analysis]
14 Jeong H, Moon Y, Park E, Lee H. Solar Coronal Magnetic Field Extrapolation from Synchronic Data with AI-generated Farside. ApJ 2020;903:L25. [DOI: 10.3847/2041-8213/abc255] [Cited by in Crossref: 8] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
15 Nishizuka N, Kubo Y, Sugiura K, Den M, Ishii M. Reliable Probability Forecast of Solar Flares: Deep Flare Net-Reliable (DeFN-R). ApJ 2020;899:150. [DOI: 10.3847/1538-4357/aba2f2] [Cited by in Crossref: 8] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
16 Deshmukh V, Berger TE, Bradley E, Meiss JD. Leveraging the mathematics of shape for solar magnetic eruption prediction. J Space Weather Space Clim 2020;10:13. [DOI: 10.1051/swsc/2020014] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 4.0] [Reference Citation Analysis]
17 Li X, Zheng Y, Wang X, Wang L. Predicting Solar Flares Using a Novel Deep Convolutional Neural Network. ApJ 2020;891:10. [DOI: 10.3847/1538-4357/ab6d04] [Cited by in Crossref: 20] [Cited by in F6Publishing: 15] [Article Influence: 10.0] [Reference Citation Analysis]
18 Yi K, Moon Y, Shin G, Lim D. Forecast of Major Solar X-Ray Flare Flux Profiles Using Novel Deep Learning Models. ApJ 2020;890:L5. [DOI: 10.3847/2041-8213/ab701b] [Cited by in Crossref: 8] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
19 Zheng Y, Li X, Wang X. Solar Flare Prediction with the Hybrid Deep Convolutional Neural Network. ApJ 2019;885:73. [DOI: 10.3847/1538-4357/ab46bd] [Cited by in Crossref: 15] [Cited by in F6Publishing: 12] [Article Influence: 5.0] [Reference Citation Analysis]
20 Lim D, Moon Y, Park E, Park J, Lee K, Lee J, Jang S. Ensemble Forecasting of Major Solar Flares with Short-, Mid-, and Long-term Active Region Properties. ApJ 2019;885:35. [DOI: 10.3847/1538-4357/ab45e7] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
21 Park E, Moon Y, Lee J, Kim R, Lee H, Lim D, Shin G, Kim T. Generation of Solar UV and EUV Images from SDO /HMI Magnetograms by Deep Learning. ApJ 2019;884:L23. [DOI: 10.3847/2041-8213/ab46bb] [Cited by in Crossref: 17] [Cited by in F6Publishing: 10] [Article Influence: 5.7] [Reference Citation Analysis]
22 Campi C, Benvenuto F, Massone AM, Bloomfield DS, Georgoulis MK, Piana M. Feature Ranking of Active Region Source Properties in Solar Flare Forecasting and the Uncompromised Stochasticity of Flare Occurrence. ApJ 2019;883:150. [DOI: 10.3847/1538-4357/ab3c26] [Cited by in Crossref: 24] [Cited by in F6Publishing: 20] [Article Influence: 8.0] [Reference Citation Analysis]