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:

Analysis of Galactic cirrus filaments in HSC-SSP high-resolution deep images using artificial neural networks

Denis M. Poliakov, Anton A. Smirnov, Sergey S. Savchenko, Alexander A. Marchuk, Aleksandr V. Mosenkov, Vladimir B. Il’in, George A. Gontcharov, Daria G. Turichina and Andrey D. Panasyuk
Astronomy and Computing 55 101075 (2026)
https://doi.org/10.1016/j.ascom.2026.101075

Predicting Dust Temperature from Molecular Line Data Using Machine Learning

Tenta Dougome, Yoshito Shimajiri, Kazuya Saigo, Sanemichi Takahashi, Miyu Kido, Shu Ishibashi and Shigehisa Takakuwa
The Astrophysical Journal 998 (1) 29 (2026)
https://doi.org/10.3847/1538-4357/ae2ec3

Interstellar Filament Detection and Characterization: Methods and Implications for Studies of the Magnetized Interstellar Medium

Dana Alina
Galaxies 14 (3) 53 (2026)
https://doi.org/10.3390/galaxies14030053

Sutra: An Integrated Framework for Identification and Characterization of Filaments in the Interstellar Medium

Shivam Kumaran, Ushasi Bhowmick, Vipin Kumar, Manish Chauhan, Munn Vinayak Shukla and Mehul R. Pandya
The Astronomical Journal 172 (1) 36 (2026)
https://doi.org/10.3847/1538-3881/ae75db

Semantic segmentation of hyperspectral data for identifying mineral alterations in the Kuhpanj porphyry copper deposit using an improved U-Net architecture

Puyan Javandel, Nader Fathianpour and Seyed Hassan Tabatabaei
Applied Earth Science: Transactions of the Institutions of Mining and Metallurgy (2026)
https://doi.org/10.1177/25726838261460116

Deep Learning for Position Angle Quantification Applied to Interstellar Filaments

Temirkul Umetaliev, Dana Alina and Anel Salmenova
The Astronomical Journal 170 (4) 207 (2025)
https://doi.org/10.3847/1538-3881/adf858

Bridging gaps with computer vision: AI in (bio)medical imaging and astronomy

S. Rezaei, A. Chegeni, A. Javadpour, A. VafaeiSadr, L. Cao, H. Röttgering and M. Staring
Astronomy and Computing 51 100921 (2025)
https://doi.org/10.1016/j.ascom.2024.100921

Fuzzy Galaxies or Cirrus? Decomposition of Galactic Cirrus in Deep Wide-field Images

Qing 青 Liu 刘, Roberto Abraham, Peter G. Martin, William P. Bowman, Pieter van Dokkum, Shany Danieli, Ekta Patel, Steven R. Janssens, Zili Shen, Seery Chen, Ananthan Karunakaran, Michael A. Keim, Deborah Lokhorst, Imad Pasha and Douglas L. Welch
The Astrophysical Journal 979 (2) 175 (2025)
https://doi.org/10.3847/1538-4357/ad9b25

A deep neural network approach to compact source removal

M. Madarász, G. Marton, I. Gezer, S. Lehner, J. Roquette, M. Audard, D. Hernandez and O. Dionatos
Astronomy & Astrophysics 696 A37 (2025)
https://doi.org/10.1051/0004-6361/202453262

Comparing the morphology of molecular clouds without supervision

Pablo Richard, Erwan Allys, François Levrier, Antoine Gusdorf and Constant Auclair
Astronomy & Astrophysics 696 A217 (2025)
https://doi.org/10.1051/0004-6361/202451493

The role of magnetic field and stellar feedback in the evolution of filamentary structures in collapsing star-forming clouds

P. Suin, D. Arzoumanian, A. Zavagno and P. Hennebelle
Astronomy & Astrophysics 698 A119 (2025)
https://doi.org/10.1051/0004-6361/202553795

Transfer learning for galaxy feature detection: Finding giant star-forming clumps in low-redshift galaxies using Faster Region-based Convolutional Neural Network

Jürgen J Popp, Hugh Dickinson, Stephen Serjeant, Mike Walmsley, Dominic Adams, Lucy Fortson, Kameswara Mantha, Vihang Mehta, James M Dawson, Sandor Kruk and Brooke Simmons
RAS Techniques and Instruments 3 (1) 174 (2024)
https://doi.org/10.1093/rasti/rzae013

The Giant Molecular Cloud G148.24+00.41: gas properties, kinematics, and cluster formation at the nexus of filamentary flows

Vineet Rawat, M R Samal, D L Walker, et al.
Monthly Notices of the Royal Astronomical Society 528 (2) 2199 (2024)
https://doi.org/10.1093/mnras/stae060

Pierre Janin-Potiron, Raoul Cañameras, Benoit Neichel, Morgan Gray, Franck Marchis, Ryan Lambert, Fabien Quere, Guillaume Blaclard, Arnaud Malvache, Olivier Beltramo-Martin, Julien Cantegreil, Paul Boutte, Yannis Zancanaro, Antoine Gervail, Carlos M. Correia, Heather K. Marshall, Jason Spyromilio and Tomonori Usuda
142 (2024)
https://doi.org/10.1117/12.3018639

Understanding the relative importance of magnetic field, gravity, and turbulence in star formation at the hub of the giant molecular cloud G148.24+00.41

Vineet Rawat, M R Samal, Chakali Eswaraiah, et al.
Monthly Notices of the Royal Astronomical Society 528 (2) 1460 (2024)
https://doi.org/10.1093/mnras/stae053

JCMT 850 μm Continuum Observations of Density Structures in the G35 Molecular Complex

Xianjin Shen, Hong-Li Liu, Zhiyuan Ren, Anandmayee Tej, Di Li, Hauyu Baobab Liu, Gary A. Fuller, Jinjin Xie, Sihan Jiao, Aiyuan Yang, Patrick M. Koch, Fengwei Xu, Patricio Sanhueza, Pham Ngoc Diep, Nicolas Peretto, R. K. Yadav, Busaba H. Kramer, Koichiro Sugiyama, Mark G. Rawlings, Chang Won Lee, Ken’ichi Tatematsu, Daniel Harsono, David Eden, Woojin Kwon, Chao-Wei Tsai, et al.
The Astrophysical Journal 974 (2) 239 (2024)
https://doi.org/10.3847/1538-4357/ad6a5f

Supervised machine learning on Galactic filaments

L. Berthelot, A. Zavagno, T. Artières, F.-X. Dupé, M. Gray, D. Russeil, E. Schisano and D. Arzoumanian
Astronomy & Astrophysics 692 A41 (2024)
https://doi.org/10.1051/0004-6361/202450828

The problem of dust attenuation in photometric decomposition of edge-on galaxies and possible solutions

Sergey S Savchenko, Denis M Poliakov, Aleksandr V Mosenkov, et al.
Monthly Notices of the Royal Astronomical Society 524 (3) 4729 (2023)
https://doi.org/10.1093/mnras/stad2189

Investigating the Globally Collapsing Hub–Filament Cloud G326.611+0.811

Yu-Xin He, Hong-Li Liu, Xin-Di Tang, et al.
The Astrophysical Journal 957 (2) 61 (2023)
https://doi.org/10.3847/1538-4357/acf766

Predicting reliable H2 column density maps from molecular line data using machine learning

Yoshito Shimajiri, Yasutomo Kawanishi, Shinji Fujita, et al.
Monthly Notices of the Royal Astronomical Society 526 (1) 966 (2023)
https://doi.org/10.1093/mnras/stad2715