Publication detail

Classification of Spectra of Emission Line Stars Using Machine Learning Techniques

VRÁBELOVÁ, P. ŠKODA, P. VÁŽNÝ, J.

Original Title

Classification of Spectra of Emission Line Stars Using Machine Learning Techniques

Type

journal article - other

Language

English

Original Abstract

The paper deals with classification and clustering of emission-line spectra of Be stars using discrete wavelet transform (DWT), PCA, and support vector machines (SVM).

Keywords

Be star, stellar spectrum, feature extraction, dimension reduction, discrete wavelet transform, classification, support vector machines (SVM), clustering

Authors

VRÁBELOVÁ, P.; ŠKODA, P.; VÁŽNÝ, J.

RIV year

2014

Released

31. 12. 2013

ISBN

1476-8186

Periodical

International Journal of Automation and Computing

Year of study

11

Number

3

State

United States of America

Pages from

265

Pages to

273

Pages count

10

URL

https://www.fit.vut.cz/research/publication/10415/

BibTex

@article{BUT111438,
  author="Pavla {Vrábelová} and Petr {Škoda} and Jaroslav {Vážný}",
  title="Classification of Spectra of Emission Line Stars Using Machine Learning Techniques",
  journal="International Journal of Automation and Computing",
  year="2013",
  volume="11",
  number="3",
  pages="265--273",
  issn="1476-8186",
  url="https://www.fit.vut.cz/research/publication/10415/"
}