Inferring depth-dependent plasma motions from surface observations using the DeepVel neural network
J. Space Weather Space Clim., 11 (2021) 9
Published online: 2021-01-29
Articles citing this article
The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).
Cited article:
This article has been cited by the following article(s):
Transverse Velocity Field Measurement of Solar High-resolution Images Based on Unsupervised Deep Learning
Zhen-Hong Shang, Long Chen, Zhen-Ping Qiang, Yi Bi and Run-Xin LiResearch in Astronomy and Astrophysics 25 (3) 035020 (2025)
https://doi.org/10.1088/1674-4527/adbc38
Recovering coherent flow structures in active regions using machine learning
Matthew G Lennard, Suzana S A Silva, Benoit Tremblay, Andrés Asensio Ramos, Gary Verth, Istvan Ballai, Haruhisa Iijima, Hideyuki Hotta, Matthias Rempel, Sung-Hong Park and Viktor FedunMonthly Notices of the Royal Astronomical Society 539 (3) 2498 (2025)
https://doi.org/10.1093/mnras/staf576
Quantifying Poynting Flux in the Quiet Sun Photosphere
Dennis Tilipman, Maria Kazachenko, Benoit Tremblay, Ivan Milić, Valentin Martínez Pillet and Matthias RempelThe Astrophysical Journal 956 (2) 83 (2023)
https://doi.org/10.3847/1538-4357/ace621
Multi-scale deep learning for estimating horizontal velocity fields on the solar surface
Ryohtaroh T. Ishikawa, Motoki Nakata, Yukio Katsukawa, Youhei Masada and Tino L. RiethmüllerAstronomy & Astrophysics 658 A142 (2022)
https://doi.org/10.1051/0004-6361/202141743
Intensification of magnetic field in merging magnetic flux tubes driven by supergranular vortical flows
Abraham C-L Chian, Erico L Rempel, Suzana S A Silva, Luis Bellot Rubio and Milan GošićMonthly Notices of the Royal Astronomical Society 518 (4) 4930 (2022)
https://doi.org/10.1093/mnras/stac3352