Tan, Lei https://orcid.org/0000-0001-6215-9242
Mei, Ying https://orcid.org/0000-0002-7960-9251
Liu, Zhicun https://orcid.org/0000-0002-1802-6917
Luo, Yangping https://orcid.org/0000-0003-3736-6076
Deng, Hui https://orcid.org/0000-0002-8765-3906
Wang, Feng https://orcid.org/0000-0002-9847-7805
Deng, Linhua
Liu, Chao https://orcid.org/0000-0002-1802-6917
Funding for this research was provided by:
The National SKA Program of China (No. 2020SKA0110300)
The National Science Foundation for Young Scholars (No. 11903009)
The Joint Research Fund in Astronomy under cooperative agreement between the National Natural Science Foundation of China (NSFC) and the Chinese Academy of Sciences (No. U1831204)
Funds for International Cooperation and Exchange of the National Natural Science Foundation of China (No. 11961141001)
The National Science Foundation of China (No. 12173028)
The National key Research Project and Development Program of China (No. 2018YFA0404603)
Fundamental and Application Research Project of Guangzhou (No. 202102020677)
Article Title: A Robust Identification Method for Hot Subdwarfs Based on Deep Learning
Journal Title: The Astrophysical Journal Supplement Series
Article Type: paper
Copyright Information: © 2022. The Author(s). Published by the American Astronomical Society.
Publication dates
Date Received: 2021-11-03
Date Accepted: 2022-01-18
Online publication date: 2022-02-17