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).
Subpixel segmentation of borehole fractures from low resolution Doppler ultrasound images using machine learning
Shivanandan Indimath, Sigurd Vangen Wifstad, Vincent Bryon, Bjarne Rosvoll Bøklepp, Lasse Lovstakken, Jørgen Avdal, Stefano Fiorentini and Svein-Erik Måsøy Geoenergy Science and Engineering 235 212703 (2024) https://doi.org/10.1016/j.geoen.2024.212703
3D non-LTE modeling of the stellar center-to-limb variation for transmission spectroscopy studies
G. Canocchi, K. Lind, C. Lagae, A. G. M. Pietrow, A. M. Amarsi, D. Kiselman, O. Andriienko and H. J. Hoeijmakers Astronomy & Astrophysics 683 A242 (2024) https://doi.org/10.1051/0004-6361/202347858
A Data-constrained Analysis for Joule Heating as a Solar Active Region Atmosphere Heating Mechanism. I. Sunspot Umbral Light Bridge
M. S. Yalim, M. Frisse, C. Beck, D. P. Choudhary, A. Prasad, S. S. Nayak and G. P. Zank The Astrophysical Journal 973(1) 58 (2024) https://doi.org/10.3847/1538-4357/ad5e75
Physically Motivated Deep Learning to Superresolve and Cross Calibrate Solar Magnetograms
Andrés Muñoz-Jaramillo, Anna Jungbluth, Xavier Gitiaux, Paul J. Wright, Carl Shneider, Shane A. Maloney, Atılım Güneş Baydin, Yarin Gal, Michel Deudon and Freddie Kalaitzis The Astrophysical Journal Supplement Series 271(2) 46 (2024) https://doi.org/10.3847/1538-4365/ad12c2
Super-Resolution of SOHO/MDI Magnetograms of Solar Active Regions Using SDO/HMI Data and an Attention-Aided Convolutional Neural Network
Morphological evidence for nanoflares heating warm loops in the solar corona
Yi Bi, Jia-Yan Yang, Ying Qin, Zheng-Ping Qiang, Jun-Chao Hong, Bo Yang, Zhe Xu, Hui Liu and Kai-Fan Ji Astronomy & Astrophysics 679 A9 (2023) https://doi.org/10.1051/0004-6361/202346944
2022 Review of Data-Driven Plasma Science
Rushil Anirudh, Rick Archibald, M. Salman Asif, Markus M. Becker, Sadruddin Benkadda, Peer-Timo Bremer, Rick H. S. Budé, C. S. Chang, Lei Chen, R. M. Churchill, Jonathan Citrin, Jim A. Gaffney, Ana Gainaru, Walter Gekelman, Tom Gibbs, Satoshi Hamaguchi, Christian Hill, Kelli Humbird, Sören Jalas, Satoru Kawaguchi, Gon-Ho Kim, Manuel Kirchen, Scott Klasky, John L. Kline, Karl Krushelnick, et al. IEEE Transactions on Plasma Science 51(7) 1750 (2023) https://doi.org/10.1109/TPS.2023.3268170
Venus’ Cloud-Tracked Winds Using Ground- and Space-Based Observations with TNG/NICS and VEx/VIRTIS
Pedro Machado, Javier Peralta, José E. Silva, Francisco Brasil, Ruben Gonçalves and Miguel Silva Atmosphere 13(2) 337 (2022) https://doi.org/10.3390/atmos13020337
Subarcsecond Imaging of a Solar Active Region Filament With ALMA and IRIS
Mapping Solar X-Ray Images from SDO/AIA EUV Images by Deep Learning
Junchao Hong, Hui Liu, Yi Bi, Zhe Xu, Bo Yang, Jiayan Yang, Yang Su, Yuehan Xia and Kaifan Ji The Astrophysical Journal 915(2) 96 (2021) https://doi.org/10.3847/1538-4357/ac01d5
Blind restoration of solar images via the Channel Sharing Spatio-temporal Network
Detection of the Strongest Magnetic Field in a Sunspot Light Bridge
J. S. Castellanos Durán, Andreas Lagg, Sami K. Solanki and Michiel van Noort The Astrophysical Journal 895(2) 129 (2020) https://doi.org/10.3847/1538-4357/ab83f1
Super-resolution of SDO/HMI Magnetograms Using Novel Deep Learning Methods
Sumiaya Rahman, Yong-Jae Moon, Eunsu Park, Ashraf Siddique, Il-Hyun Cho and Daye Lim The Astrophysical Journal Letters 897(2) L32 (2020) https://doi.org/10.3847/2041-8213/ab9d79
A deep learning virtual instrument for monitoring extreme UV solar spectral irradiance
Alexandre Szenicer, David F. Fouhey, Andres Munoz-Jaramillo, Paul J. Wright, Rajat Thomas, Richard Galvez, Meng Jin and Mark C. M. Cheung Science Advances 5(10) (2019) https://doi.org/10.1126/sciadv.aaw6548
Solar image denoising with convolutional neural networks