Result Details

Classification of Spectra of Emission Line Stars Using Machine Learning Techniques

VRÁBELOVÁ, P.; ŠKODA, P.; VÁŽNÝ, J. Classification of Spectra of Emission Line Stars Using Machine Learning Techniques. International Journal of Automation and Computing, 2013, vol. 11, no. 3, p. 265-273. ISSN: 1476-8186.
Type
journal article
Language
English
Authors
Vrábelová Pavla, Ing., DIFS (FIT)
Škoda Petr, RNDr., Ph.D.
Vážný Jaroslav
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
Published
2013
Pages
265–273
Journal
International Journal of Automation and Computing, vol. 11, no. 3, ISSN 1476-8186
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/"
}
Files
Projects
Advanced recognition and presentation of multimedia data, BUT, Vnitřní projekty VUT, FIT-S-11-2, start: 2011-01-01, end: 2013-12-31, completed
Security-Oriented Research in Information Technology, MŠMT, Institucionální prostředky SR ČR (např. VZ, VC), MSM0021630528, start: 2007-01-01, end: 2013-12-31, running
Research groups
Information and Database Systems Research Group (RG IS)
Departments
Department of Information Systems (DIFS)
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