Enhanced astronomical source classification with integration of attention mechanisms and vision transformers-Reference-Cited by-同舟云学术

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Enhanced astronomical source classification with integration of attention mechanisms and vision transformers

Published:2024-08 Issue:8 Volume:369 Page:
ISSN:0004-640X
Container-title:Astrophysics and Space Science
language:en
Short-container-title:Astrophys Space Sci

Author:

Bhavanam Srinadh Reddy,Channappayya Sumohana S.,P. K Srijith,Desai Shantanu

Funder

Tata Consultancy Services,India

Department of Science and Technology, Ministry of Science and Technology, India

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10509-024-04357-9.pdf

Reference79 articles.

1. Abraham, S., Aniyan, A., Kembhavi, A.K., et al.: Detection of bars in galaxies using a deep convolutional neural network. Mon. Not. R. Astron. Soc. 477(1), 894–903 (2018)

2. Ahumada, R., Prieto, C.A., Almeida, A., et al.: The 16th data release of the sloan digital sky surveys: first release from the apogee-2 southern survey and full release of eboss spectra. Astrophys. J. Suppl. Ser. 249(1), 3 (2020)

3. Ball, N.M., Brunner, R.J.: Data mining and machine learning in astronomy. Int. J. Mod. Phys. D 19(07), 1049–1106 (2010)

4. Barchi, P.H., de Carvalho, R., Rosa, R.R., et al.: Machine and deep learning applied to galaxy morphology-a comparative study. Astron. Comput. 30, 100334 (2020)

5. Baron, D.: Machine learning in astronomy: a practical overview (2019). arXiv:1904.07248. ArXiv preprint

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