Stellar classification from single-band imaging using machine learning

Stellar classification from single-band imaging using machine learning T. Kuntzer, M. Tewes1†, F. Courbin1† 1EPFL, Switzerland †Listed affiliation is based on previous publications and was not specified in this preprint. ArXiv #: 1605.03201 (PDF, PS, ADS, Papers, Other) Comments: 10 pages, 9 figures, 2 tables, accepted in A&A Originally posted by astro-ph from Unaffiliated on 05/11/2016 IM 7 ‘s: Brian Siana (UCR), rjoseph (EPFL – UniGe), revaz (EPFL – UniGe), Vivien Bonvin (EPFL – UniGe), kstringer (Texas A&M), otelford (University of Washington), mlam (Cornell) Information on the spectral types of stars is of great interest in view of the exploitation of space-based imaging surveys. In this article, we investigate the classification of stars into spectral types using only the shape of their diffraction pattern in a single broad-band image. We…


Link to Full Article: Stellar classification from single-band imaging using machine learning