Principal component analysis neural network hybrid classification approach for galaxies images

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86096575" target="_blank" >RIV/61989100:27240/14:86096575 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/14:86096575
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-01781-5_21" target="_blank" >http://dx.doi.org/10.1007/978-3-319-01781-5_21</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-01781-5_21" target="_blank" >10.1007/978-3-319-01781-5_21</a>

Result language
angličtina
Original language name
Principal component analysis neural network hybrid classification approach for galaxies images
Original language description
This article presents an automatic hybrid approach for galaxies images classification based on principal component analysis (PCA) neural network and moment-based features extraction algorithms. The proposed approach is consisted of four phases; namely image denoising, feature extraction, reduct generation, and classification phases. For the denoising phase, noise pixels are removed from input images, then input galaxy image is normalized to a uniform scale and Hu seven invariant moment algorithm is applied to reduce the dimensionality of the feature space during the feature extraction phase. Subsequently, for reduct generation phase, attributes in the information system table that is more important to the knowledge is generated as a subset of attributes. Rough set is used as feature reduction approach. The subset of attributed, which is called a reduct, is fully characterizing the knowledge in the database. Finally, during the classification phase, principal component analysis neural n
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Advances in Intelligent Systems and Computing. Volume 237
ISBN
978-3-319-01780-8
ISSN
2194-5357
e-ISSN
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Number of pages
13
Pages from-to
225-237
Publisher name
Springer
Place of publication
Basel
Event location
Ostrava
Event date
Aug 22, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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