Automatic classification of eclipsing binary stars using deep learning methods-Reference-Cited by-同舟云学术

Automatic classification of eclipsing binary stars using deep learning methods

Published:2021-07 Issue: Volume:36 Page:100488
ISSN:2213-1337
Container-title:Astronomy and Computing
language:en
Short-container-title:Astronomy and Computing

Author:

Čokina M.,Maslej-Krešňáková V.,Butka P.^ORCID,Parimucha Š.^ORCID

Funder

Agentúra na Podporu Výskumu a Vývoja

Vedecká Grantová Agentúra MŠVVaŠ SR a SAV

Publisher

Elsevier BV

Subject

Computer Science Applications,Astronomy and Astrophysics,Space and Planetary Science

Reference40 articles.

1. Tensorflow: A system for large-scale machine learning;Abadi,2016

2. Normal and abnormal binary frequencies;Abt;Annu. Rev. Astron. Astrophys.,1983

3. Systematic discovery and classification of TESS eclipsing binaries;Birky;Bull. Am. Astron. Soc.,2020

4. Castelli, F., Kurucz, R., 2004. New grids of ATLAS9 model atmospheres. In: Proceedings of the IAU Symp. No 210 - Modelling of Stellar Atmospheres, Poster A20, URL: https://arxiv.org/abs/astro-ph/0405087.

5. Keras;Chollet,2015

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