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Search for the edge-on galaxies using an artificial neural network. / Savchenko, S. S.; Makarov, D. I.; Antipova, A. V.; Tikhonenko, I. S.

в: Astronomy and Computing, Том 46, 100771, 01.01.2024.

Результаты исследований: Научные публикации в периодических изданияхстатьяРецензирование

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Savchenko, S. S. ; Makarov, D. I. ; Antipova, A. V. ; Tikhonenko, I. S. / Search for the edge-on galaxies using an artificial neural network. в: Astronomy and Computing. 2024 ; Том 46.

BibTeX

@article{10fad0be82a2467392ffbad0de051b0d,
title = "Search for the edge-on galaxies using an artificial neural network",
abstract = "We present an application of an artificial neural network methodology to a modern wide-field sky survey Pan-STARRS1 in order to build a high-quality sample of disk galaxies visible in edge-on orientation. Such galaxies play an important role in the study of the vertical distribution of stars, gas and dust, which is usually not available to study in other galaxies outside the Milky Way. We give a detailed description of the network architecture and the learning process. The method demonstrates good effectiveness with detection rate about 97% and it works equally well for galaxies over a wide range of brightnesses and sizes, which resulted in a creation of a catalogue of edge-on galaxies with 105 of objects. The catalogue is published on-line with an open access.",
keywords = "Methods: data analysis, Catalogs, Galaxies: general, Software: general, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Astrophysics of Galaxies",
author = "Savchenko, {S. S.} and Makarov, {D. I.} and Antipova, {A. V.} and Tikhonenko, {I. S.}",
year = "2024",
month = jan,
day = "1",
doi = "10.1016/j.ascom.2023.100771",
language = "русский",
volume = "46",
journal = "Astronomy and Computing",
issn = "2213-1337",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Search for the edge-on galaxies using an artificial neural network

AU - Savchenko, S. S.

AU - Makarov, D. I.

AU - Antipova, A. V.

AU - Tikhonenko, I. S.

PY - 2024/1/1

Y1 - 2024/1/1

N2 - We present an application of an artificial neural network methodology to a modern wide-field sky survey Pan-STARRS1 in order to build a high-quality sample of disk galaxies visible in edge-on orientation. Such galaxies play an important role in the study of the vertical distribution of stars, gas and dust, which is usually not available to study in other galaxies outside the Milky Way. We give a detailed description of the network architecture and the learning process. The method demonstrates good effectiveness with detection rate about 97% and it works equally well for galaxies over a wide range of brightnesses and sizes, which resulted in a creation of a catalogue of edge-on galaxies with 105 of objects. The catalogue is published on-line with an open access.

AB - We present an application of an artificial neural network methodology to a modern wide-field sky survey Pan-STARRS1 in order to build a high-quality sample of disk galaxies visible in edge-on orientation. Such galaxies play an important role in the study of the vertical distribution of stars, gas and dust, which is usually not available to study in other galaxies outside the Milky Way. We give a detailed description of the network architecture and the learning process. The method demonstrates good effectiveness with detection rate about 97% and it works equally well for galaxies over a wide range of brightnesses and sizes, which resulted in a creation of a catalogue of edge-on galaxies with 105 of objects. The catalogue is published on-line with an open access.

KW - Methods: data analysis

KW - Catalogs

KW - Galaxies: general

KW - Software: general

KW - Astrophysics - Instrumentation and Methods for Astrophysics

KW - Astrophysics - Astrophysics of Galaxies

U2 - 10.1016/j.ascom.2023.100771

DO - 10.1016/j.ascom.2023.100771

M3 - статья

VL - 46

JO - Astronomy and Computing

JF - Astronomy and Computing

SN - 2213-1337

M1 - 100771

ER -

ID: 124376672