Work

Machine learning technique for morphological classification of galaxies from the SDSS. III. Image-based inference of detailed features

Year: 2022

Type: preprint

Abstract: This paper follows series of our works on the applicability of various machine learning methods to the morphological galaxy classification (Vavilova et al., 2021, 2022). We exploited the sample of 315776 SDSS DR9 galaxies with absolute stellar magnitudes of -24m

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2209.12194

Authors: Khramtsov, V., Vavilova, I. B., Dobrycheva, D. V., Vasylenko, M. Yu., Melnyk, O. V., Elyiv, A. A., Akhmetov, V. S., Dmytrenko, A. M.

Institutions: V. N. Karazin Kharkiv National University, Main Astronomical Observatory

Language: English

Topic: Galaxies: Formation, Evolution, Phenomena

Subfield: Astronomy and Astrophysics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

Funders: National Aeronautics and Space Administration, Alfred P. Sloan Foundation, California Institute of Technology, Jet Propulsion Laboratory, Astrophysics Division

OpenAlex ID: W4297435693

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Cited by: 2

Related to: 10