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StellarGAN: Classifying Stellar Spectra with Generative Adversarial Networks in SDSS and APOGEE Sky Surveys
Wei Liu, Shuo Cao, Xian-Chuan Yu, Meng Zhu, Marek Biesiada, Jiawen Yao and Minghao Du The Astrophysical Journal Supplement Series 271(2) 53 (2024) https://doi.org/10.3847/1538-4365/ad29ef
SFNet: Stellar Feature Network with CWT for Stellar Spectra Recognition
F. Arenou, C. Babusiaux, M. A. Barstow, S. Faigler, A. Jorissen, P. Kervella, T. Mazeh, N. Mowlavi, P. Panuzzo, J. Sahlmann, S. Shahaf, A. Sozzetti, N. Bauchet, Y. Damerdji, P. Gavras, P. Giacobbe, E. Gosset, J.-L. Halbwachs, B. Holl, M. G. Lattanzi, N. Leclerc, T. Morel, D. Pourbaix, P. Re Fiorentin, G. Sadowski, et al. Astronomy & Astrophysics 674 A34 (2023) https://doi.org/10.1051/0004-6361/202243782
Stellar classification with convolutional neural networks and photometric images: a new catalogue of 50 million SDSS stars without spectra
Spectral Classification and Particular Spectra Identification Based on Data Mining
Peng Yang, Guowei Yang, Fanlong Zhang, Bing Jiang and Mengxin Wang Archives of Computational Methods in Engineering 28(3) 917 (2021) https://doi.org/10.1007/s11831-020-09401-9
International Conference on Applications and Techniques in Cyber Intelligence ATCI 2019
Yongjian Zhao Advances in Intelligent Systems and Computing, International Conference on Applications and Techniques in Cyber Intelligence ATCI 2019 1017 135 (2020) https://doi.org/10.1007/978-3-030-25128-4_18
Application of Artificial Neural Networks for the Automatic Spectral Classification
Edgar Vilavicencio-Arcadia, Silvana G. Navarro, Luis J. Corral, et al. Mathematical Problems in Engineering 2020 1 (2020) https://doi.org/10.1155/2020/1751932
International Conference on Applications and Techniques in Cyber Intelligence ATCI 2019
Yongjian Zhao Advances in Intelligent Systems and Computing, International Conference on Applications and Techniques in Cyber Intelligence ATCI 2019 1017 738 (2020) https://doi.org/10.1007/978-3-030-25128-4_91
Application of convolutional neural networks for stellar spectral classification
Kaushal Sharma, Ajit Kembhavi, Aniruddha Kembhavi, et al. Monthly Notices of the Royal Astronomical Society 491(2) 2280 (2020) https://doi.org/10.1093/mnras/stz3100
Pattern recognition in time series for space missions: A rosetta magnetic field case study
Stellar spectral interpolation using machine learning
Kaushal Sharma, Harinder P Singh, Ranjan Gupta, et al. Monthly Notices of the Royal Astronomical Society 496(4) 5002 (2020) https://doi.org/10.1093/mnras/staa1809
Machine learning in APOGEE
Rafael Garcia-Dias, Carlos Allende Prieto, Jorge Sánchez Almeida and Pedro Alonso Palicio Astronomy & Astrophysics 629 A34 (2019) https://doi.org/10.1051/0004-6361/201935223
Machine Learning Applied to Star–Galaxy–QSO Classification and Stellar Effective Temperature Regression
The Metallicity Distribution and Hot Jupiter Rate of the Kepler Field: Hectochelle High-resolution Spectroscopy for 776 Kepler Target Stars
Xueying Guo, John A. Johnson, Andrew W. Mann, Adam L. Kraus, Jason L. Curtis and David W. Latham The Astrophysical Journal 838(1) 25 (2017) https://doi.org/10.3847/1538-4357/aa6004
A new automated spectral feature extraction method and its application in spectral classification and defective spectra recovery
Evaluation of data compression techniques for the inference of stellar atmospheric parameters from high-resolution spectra
A. González-Marcos, L. M. Sarro, J. Ordieres-Meré and A. Bello-García Monthly Notices of the Royal Astronomical Society 465(4) 4556 (2017) https://doi.org/10.1093/mnras/stw3031
Stellar Spectral Classification with Locality Preserving Projections and Support Vector Machine
Distance determination to PNe using the extinction-distance method
Silvana G. Navarro, Romano L. M. Corradi and Antonio Mampaso Proceedings of the International Astronomical Union 7(S283) 460 (2011) https://doi.org/10.1017/S1743921312011921
The very large array: Design and performance of a modern synthesis radio telescope