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:

Prediction of Star Formation Rates Using an Artificial Neural Network

Ashraf Ayubinia, Jong-Hak Woo, Fatemeh Hafezianzadeh, Taehwan Kim and Changseok Kim
The Astrophysical Journal 980 (2) 177 (2025)
https://doi.org/10.3847/1538-4357/ada366

Performance Comparison of Supervised Machine Learning Methods in Classifying Celestial Objects

Maide Feyza Er and Turgay Tugay Bilgin
Black Sea Journal of Engineering and Science 7 (5) 960 (2024)
https://doi.org/10.34248/bsengineering.1517904

Radio galaxies classification system using machine learning techniques in the IoT Era

Kamil Dimililer, Hanifa Teimourian and Fadi Al-Turjman
Journal of Experimental & Theoretical Artificial Intelligence 36 (3) 357 (2024)
https://doi.org/10.1080/0952813X.2022.2080277

Identifying type II quasars at intermediate redshift with few-shot learning photometric classification

P. A. C. Cunha, A. Humphrey, J. Brinchmann, S. G. Morais, R. Carvajal, J. M. Gomes, I. Matute and A. Paulino-Afonso
Astronomy & Astrophysics 687 A269 (2024)
https://doi.org/10.1051/0004-6361/202346426

E(2)-equivariant features in machine learning for morphological classification of radio galaxies

Natalie E P Lines, Joan Font-Quer Roset and Anna M M Scaife
RAS Techniques and Instruments 3 (1) 347 (2024)
https://doi.org/10.1093/rasti/rzae022

A machine learning approach to estimate mid-infrared fluxes from WISE data

Nuria Fonseca-Bonilla, Luis Cerdán, Alberto Noriega-Crespo and Amaya Moro-Martín
Astronomy & Astrophysics 691 A271 (2024)
https://doi.org/10.1051/0004-6361/202450274

Wide Area VISTA Extra-galactic Survey (WAVES): unsupervised star-galaxy separation on the WAVES-Wide photometric input catalogue using UMAP and hdbscan

Todd L Cook, Behnood Bandi, Sam Philipsborn, Jon Loveday, Sabine Bellstedt, Simon P Driver, Aaron S G Robotham, Maciej Bilicki, Gursharanjit Kaur, Elmo Tempel, Ivan Baldry, Daniel Gruen, Marcella Longhetti, Angela Iovino, Benne W Holwerda and Ricardo Demarco
Monthly Notices of the Royal Astronomical Society 535 (3) 2129 (2024)
https://doi.org/10.1093/mnras/stae2389

Supervised star, galaxy, and QSO classification with sharpened dimensionality reduction

M. A. A. Lourens, S. C. Trager, Y. Kim, A. C. Telea and J. B. T. M. Roerdink
Astronomy & Astrophysics 690 A224 (2024)
https://doi.org/10.1051/0004-6361/202450214

Fine-grained photometric classification using multi-model fusion method with redshift estimation

Peng Cheng, Zhihui Liu, Fatemeh Zahra Zeraatgri and Liquan Mei
Journal of High Energy Astrophysics 43 198 (2024)
https://doi.org/10.1016/j.jheap.2024.07.008

Machine learning based stellar classification with highly sparse photometry data

Seán Enis Cody, Sebastian Scher, Iain McDonald, Albert Zijlstra, Emma Alexander and Nick Cox
Open Research Europe 4 29 (2024)
https://doi.org/10.12688/openreseurope.17023.1

Ensemble Learning for Stellar Classification and Radius Estimation from Multimodal Data

Zhi-Jie Deng, Sheng-Yuan Yu, A-Li Luo, Xiao Kong and Xiang-Ru Li
Research in Astronomy and Astrophysics 24 (11) 115019 (2024)
https://doi.org/10.1088/1674-4527/ad86a6

Machine learning based stellar classification with highly sparse photometry data

Seán Enis Cody, Sebastian Scher, Iain McDonald, Albert Zijlstra, Emma Alexander and Nick Cox
Open Research Europe 4 29 (2024)
https://doi.org/10.12688/openreseurope.17023.2

Applying machine learning to Galactic Archaeology: how well can we recover the origin of stars in Milky Way-like galaxies?

Andrea Sante, Andreea S Font, Sandra Ortega-Martorell, Ivan Olier and Ian G McCarthy
Monthly Notices of the Royal Astronomical Society 531 (4) 4363 (2024)
https://doi.org/10.1093/mnras/stae1398

Exploring galactic properties with machine learning

F. Z. Zeraatgari, F. Hafezianzadeh, Y.-X. Zhang, A. Mosallanezhad and J.-Y. Zhang
Astronomy & Astrophysics 688 A33 (2024)
https://doi.org/10.1051/0004-6361/202348714

Machine learning applications in studies of the physical properties of active galactic nuclei based on photometric observations

Sarah Mechbal, Markus Ackermann and Marek Kowalski
Astronomy & Astrophysics 685 A107 (2024)
https://doi.org/10.1051/0004-6361/202346557

A Multimodal Transfer Learning Method for Classifying Images of Celestial Point Sources

Bingjun Wang, Shuxin Hong, Zhiyang Yuan, A-Li Luo, Xiao Kong and Zhiqiang Zou
Publications of the Astronomical Society of the Pacific 135 (1052) 104502 (2023)
https://doi.org/10.1088/1538-3873/acfbb9

J-PLUS: galaxy-star-quasar classification for DR3

R von Marttens, V Marra, M Quartin, L Casarini, P O Baqui, A Alvarez-Candal, F J Galindo-Guil, J A Fernández-Ontiveros, Andrés del Pino, L A Díaz-García, C López-Sanjuan, J Alcaniz, R Angulo, A J Cenarro, D Cristóbal-Hornillos, R Dupke, A Ederoclite, C Hernández-Monteagudo, A Marín-Franch, M Moles, L Sodré, J Varela and H Vázquez Ramió
Monthly Notices of the Royal Astronomical Society 527 (2) 3347 (2023)
https://doi.org/10.1093/mnras/stad3373

Machine learning-based photometric classification of galaxies, quasars, emission-line galaxies, and stars

Fatemeh Zahra Zeraatgari, Fatemeh Hafezianzadeh, Yanxia Zhang, Liquan Mei, Ashraf Ayubinia, Amin Mosallanezhad and Jingyi Zhang
Monthly Notices of the Royal Astronomical Society 527 (3) 4677 (2023)
https://doi.org/10.1093/mnras/stad3436

Selection of powerful radio galaxies with machine learning

R. Carvajal, I. Matute, J. Afonso, R. P. Norris, K. J. Luken, P. Sánchez-Sáez, P. A. C. Cunha, A. Humphrey, H. Messias, S. Amarantidis, D. Barbosa, H. A. Cruz, H. Miranda, A. Paulino-Afonso and C. Pappalardo
Astronomy & Astrophysics 679 A101 (2023)
https://doi.org/10.1051/0004-6361/202245770

Photometric classification of quasars from ALHAMBRA survey using random forest

Benjamín Arroquia-Cuadros, Néstor Sánchez, Vicent Gómez, et al.
Astronomy & Astrophysics 673 A48 (2023)
https://doi.org/10.1051/0004-6361/202245531

Stellar classification with convolutional neural networks and photometric images: a new catalogue of 50 million SDSS stars without spectra

Jing-Hang Shi, Bo Qiu, A-Li Luo, et al.
Monthly Notices of the Royal Astronomical Society 520 (2) 2269 (2023)
https://doi.org/10.1093/mnras/stad255

Stellar Dynamical Modeling—Counting Conserved Quantities

Richard J. Long, Shude Mao and Yougang Wang
Research in Astronomy and Astrophysics 23 (5) 055018 (2023)
https://doi.org/10.1088/1674-4527/acc152

Improving machine learning-derived photometric redshifts and physical property estimates using unlabelled observations

A Humphrey, P A C Cunha, A Paulino-Afonso, et al.
Monthly Notices of the Royal Astronomical Society 520 (1) 305 (2023)
https://doi.org/10.1093/mnras/stac3596

Random forest Algorithm for the Classification of Spectral Data of Astronomical Objects

José-Luis Solorio-Ramírez, Raúl Jiménez-Cruz, Yenny Villuendas-Rey and Cornelio Yáñez-Márquez
Algorithms 16 (6) 293 (2023)
https://doi.org/10.3390/a16060293

The LSST AGN Data Challenge: Selection Methods

Đorđe V. Savić, Isidora Jankov, Weixiang Yu, Vincenzo Petrecca, Matthew J. Temple, Qingling Ni, Raphael Shirley, Andjelka B. Kovačević, Mladen Nikolić, Dragana Ilić, Luka Č. Popović, Maurizio Paolillo, Swayamtrupta Panda, Aleksandra Ćiprijanović and Gordon T. Richards
The Astrophysical Journal 953 (2) 138 (2023)
https://doi.org/10.3847/1538-4357/ace31a

Beyond the Local Volume. I. Surface Densities of Ultracool Dwarfs in Deep HST/WFC3 Parallel Fields

Christian Aganze, Adam J. Burgasser, Mathew Malkan, Christopher A. Theissen, Roberto A. Tejada Arevalo, Chih-Chun Hsu, Daniella C. Bardalez Gagliuffi, Russell E. Ryan and Benne Holwerda
The Astrophysical Journal 924 (2) 114 (2022)
https://doi.org/10.3847/1538-4357/ac35ea

Applying Random Forest Classification to Ultracool Dwarf Discovery in Deep Surveys. I. Color Classification with SDSS, UKIDSS, and WISE Photometry

Zijie Gong, Adriana Nava Vega, Eduardo Gauna Gutierrez, Arantxa Mendiola Maytorena, Carlos Verdaguer, Christian Aganze, Christopher Danner and Adam J. Burgasser
Research Notes of the AAS 6 (4) 74 (2022)
https://doi.org/10.3847/2515-5172/ac6521

Data mining techniques on astronomical spectra data – II. Classification analysis

Haifeng Yang, Lichan Zhou, Jianghui Cai, et al.
Monthly Notices of the Royal Astronomical Society 518 (4) 5904 (2022)
https://doi.org/10.1093/mnras/stac3292

Photometric identification of compact galaxies, stars, and quasars using multiple neural networks

Siddharth Chaini, Atharva Bagul, Anish Deshpande, Rishi Gondkar, Kaushal Sharma, M Vivek and Ajit Kembhavi
Monthly Notices of the Royal Astronomical Society 518 (2) 3123 (2022)
https://doi.org/10.1093/mnras/stac3336

Quasar Identification Using Multivariate Probability Density Estimated from Nonparametric Conditional Probabilities

Jenny Farmer, Eve Allen and Donald J. Jacobs
Mathematics 11 (1) 155 (2022)
https://doi.org/10.3390/math11010155

Machine-learning classification of astronomical sources: estimating F1-score in the absence of ground truth

A Humphrey, W Kuberski, J Bialek, N Perrakis, W Cools, N Nuyttens, H Elakhrass and P A C Cunha
Monthly Notices of the Royal Astronomical Society: Letters 517 (1) L116 (2022)
https://doi.org/10.1093/mnrasl/slac120

An exploration of how training set composition bias in machine learning affects identifying rare objects

S.E. Lake and C.-W. Tsai
Astronomy and Computing 40 100617 (2022)
https://doi.org/10.1016/j.ascom.2022.100617

Practical galaxy morphology tools from deep supervised representation learning

Mike Walmsley, Anna M M Scaife, Chris Lintott, et al.
Monthly Notices of the Royal Astronomical Society 513 (2) 1581 (2022)
https://doi.org/10.1093/mnras/stac525

The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar, and APOGEE-2 Data

Abdurro’uf, Katherine Accetta, Conny Aerts, Víctor Silva Aguirre, Romina Ahumada, Nikhil Ajgaonkar, N. Filiz Ak, Shadab Alam, Carlos Allende Prieto, Andrés Almeida, Friedrich Anders, Scott F. Anderson, Brett H. Andrews, Borja Anguiano, Erik Aquino-Ortíz, Alfonso Aragón-Salamanca, Maria Argudo-Fernández, Metin Ata, Marie Aubert, Vladimir Avila-Reese, Carles Badenes, Rodolfo H. Barbá, Kat Barger, Jorge K. Barrera-Ballesteros, Rachael L. Beaton, et al.
The Astrophysical Journal Supplement Series 259 (2) 35 (2022)
https://doi.org/10.3847/1538-4365/ac4414

Deep learning applications based on SDSS photometric data: detection and classification of sources

Zhendong He, Bo Qiu, A-Li Luo, et al.
Monthly Notices of the Royal Astronomical Society 508 (2) 2039 (2021)
https://doi.org/10.1093/mnras/stab2243

Estimation of Photometric Redshifts. I. Machine-learning Inference for Pan-STARRS1 Galaxies Using Neural Networks

Joongoo Lee and Min-Su Shin
The Astronomical Journal 162 (6) 297 (2021)
https://doi.org/10.3847/1538-3881/ac2e96

On the discovery of stars, quasars, and galaxies in the Southern Hemisphere with S-PLUS DR2

L Nakazono, C Mendes de Oliveira, N S T Hirata, et al.
Monthly Notices of the Royal Astronomical Society 507 (4) 5847 (2021)
https://doi.org/10.1093/mnras/stab1835

Discovery of five new Galactic symbiotic stars in the VPHAS+ survey

Stavros Akras, Denise R Gonçalves, Alvaro Alvarez-Candal and Claudio B Pereira
Monthly Notices of the Royal Astronomical Society 502 (2) 2513 (2021)
https://doi.org/10.1093/mnras/stab195

Identification of BASS DR3 sources as stars, galaxies, and quasars by XGBoost

Changhua Li, Yanxia Zhang, Chenzhou Cui, et al.
Monthly Notices of the Royal Astronomical Society 506 (2) 1651 (2021)
https://doi.org/10.1093/mnras/stab1650

Photometric selection and redshifts for quasars in the Kilo-Degree Survey Data Release 4

S. J. Nakoneczny, M. Bilicki, A. Pollo, et al.
Astronomy & Astrophysics 649 A81 (2021)
https://doi.org/10.1051/0004-6361/202039684

Attention-gating for improved radio galaxy classification

Micah Bowles, Anna M M Scaife, Fiona Porter, Hongming Tang and David J Bastien
Monthly Notices of the Royal Astronomical Society 501 (3) 4579 (2021)
https://doi.org/10.1093/mnras/staa3946

Deep Learning assessment of galaxy morphology in S-PLUS Data Release 1

C R Bom, A Cortesi, G Lucatelli, et al.
Monthly Notices of the Royal Astronomical Society 507 (2) 1937 (2021)
https://doi.org/10.1093/mnras/stab1981

Evolutionary map of the Universe (EMU): Compact radio sources in the scorpio field towards the galactic plane

S Riggi, G Umana, C Trigilio, et al.
Monthly Notices of the Royal Astronomical Society 502 (1) 60 (2021)
https://doi.org/10.1093/mnras/stab028

On Neural Architectures for Astronomical Time-series Classification with Application to Variable Stars

Sara Jamal and Joshua S. Bloom
The Astrophysical Journal Supplement Series 250 (2) 30 (2020)
https://doi.org/10.3847/1538-4365/aba8ff