Classification of Spectra of Emission Line Stars Using Machine Learning Techniques
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F13%3APU111890" target="_blank" >RIV/00216305:26230/13:PU111890 - isvavai.cz</a>
Alternative codes found
RIV/67985815:_____/14:00430487
Result on the web
<a href="http://www.fit.vutbr.cz/research/pubs/all.php?id=10415" target="_blank" >http://www.fit.vutbr.cz/research/pubs/all.php?id=10415</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Classification of Spectra of Emission Line Stars Using Machine Learning Techniques
Original language description
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).
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA13-08195S" target="_blank" >GA13-08195S: Highly Scalable Parallel and Distributed Methods of Data Processing in E-science</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Automation and Computing
ISSN
1476-8186
e-ISSN
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Volume of the periodical
11
Issue of the periodical within the volume
3
Country of publishing house
US - UNITED STATES
Number of pages
10
Pages from-to
265-273
UT code for WoS article
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EID of the result in the Scopus database
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