Identification of Interesting Objects in Large Spectral Surveys Using Highly Parallelized Machine Learning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985815%3A_____%2F17%3A00485674" target="_blank" >RIV/67985815:_____/17:00485674 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1017/S1743921317000047" target="_blank" >http://dx.doi.org/10.1017/S1743921317000047</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1017/S1743921317000047" target="_blank" >10.1017/S1743921317000047</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Identification of Interesting Objects in Large Spectral Surveys Using Highly Parallelized Machine Learning

Popis výsledku v původním jazyce

We present results of Spark-based semi-supervised machine learning of LAMOST spectra attempting to automatically identify the single and double-peak emission of H.alpha. line typical for Be and B[e] stars. The labelled sample was obtained from archive of 2m Perek telescope at Ondřejov observatory. A simple physical model of spectrograph resolution was used in domain adaptation to LAMOST training domain. The resulting list of candidates contains dozens of Be stars (some are likely yet unknown), but also a bunch of interesting objects resembling spectra of quasars and even blazars, as well as many instrumental artefacts. The verification of a nature of interesting candidates benefited considerably from cross-matching and visualisation in the Virtual Observatory environment.

Název v anglickém jazyce

Identification of Interesting Objects in Large Spectral Surveys Using Highly Parallelized Machine Learning

Popis výsledku anglicky

We present results of Spark-based semi-supervised machine learning of LAMOST spectra attempting to automatically identify the single and double-peak emission of H.alpha. line typical for Be and B[e] stars. The labelled sample was obtained from archive of 2m Perek telescope at Ondřejov observatory. A simple physical model of spectrograph resolution was used in domain adaptation to LAMOST training domain. The resulting list of candidates contains dozens of Be stars (some are likely yet unknown), but also a bunch of interesting objects resembling spectra of quasars and even blazars, as well as many instrumental artefacts. The verification of a nature of interesting candidates benefited considerably from cross-matching and visualisation in the Virtual Observatory environment.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10308 - Astronomy (including astrophysics,space science)

Projekt

<a href="/cs/project/LD15113" target="_blank" >LD15113: Aplikace umělé inteligence v astronomii</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Astroinformatics

ISBN

9781107169951

ISSN

1743-9213

e-ISSN

—

Počet stran výsledku

6

Strana od-do

180-185

Název nakladatele

Cambridge University Press

Místo vydání

Cambridge

Místo konání akce

Sorrento

Datum konání akce

19. 10. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000456314100026