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Conference papers

Object Classification in SDSS DR12

Abstract : LSST will observe ~10 billions of stars and the same number of galaxies. Since it is a non-spectroscopic survey, it is crucial to make a method to automatically separate different celestial objects from each other. Here, we use spectroscopy-photometry sample of SDSS DR12 to automatically classify stars, galaxies and QSOs using their magnitude, colour index and apparent angular size. We compute the classification efficiency of the whole sample and show that even a basic classifier can significantly separate these three different objects.
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Contributor : Sabine Starita <>
Submitted on : Monday, April 25, 2016 - 10:13:28 AM
Last modification on : Wednesday, September 16, 2020 - 4:30:45 PM


  • HAL Id : in2p3-01306591, version 1



F. Habibi. Object Classification in SDSS DR12. Future Sky Surveys and Big Data , Apr 2016, Daejeon, South Korea. ⟨in2p3-01306591⟩



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