SUPERVISED AUTOMATIC IDENTIFICATION OF EXTRAGALACTIC SOURCES IN THE WISExSUPERCOSMOS CATALOGUE
Journal Title: Odessa Astronomical Publications - Year 2017, Vol 30, Issue
Abstract
We present new catalogue of ~8,500,000 extragalactic objects as a result of automatic classification of WISE and SuperCOSMOS (SCOS) cross-identification product. The main goal is to create a set of candidates in extragalactic objects due to colour (photometric) features through machine learning techniques. Extragalactic sources were separated from stars in high-dimensional colour space using Support Vector Machine (SVM) classifier. Construction of catalogue of the extragalactic objects is based on the four important procedures: 1. Cross-identification of the WISExSCOS catalogues. 2. Training set creation (Gaia DR1 and 2MASX\XSC data). 3. Feature engineering and colour-space constructing for further learning and classification. 4. Fine-tuning of SVM and separation and classification processes. In result we got high-accuracy (~98%) algorithm for extragalactic source identification in built colour space. Product of algorithm realization is presented as photometric catalogue of the extragalactic objects and can be used for further astronomical investigations.
Authors and Affiliations
V. Khramtsov, V. S. Akhmetov
Keywords
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- EP ID EP354798
- DOI 10.18524/1810-4215.2017.30.114465
- Views 73
- Downloads 0
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