Theerapat Sangpetch1, Tossapon Boongoen1,*, Natthakan Iam-On2
CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1641-1655, 2023, DOI:10.32604/cmc.2023.026739
Abstract Attempts to determine characters of astronomical objects have been one of major and vibrant activities in both astronomy and data science fields. Instead of a manual inspection, various automated systems are invented to satisfy the need, including the classification of light curve profiles. A specific Kaggle competition, namely Photometric LSST Astronomical Time-Series Classification Challenge (PLAsTiCC), is launched to gather new ideas of tackling the abovementioned task using the data set collected from the Large Synoptic Survey Telescope (LSST) project. Almost all proposed methods fall into the supervised family with a common aim to categorize each object into one of pre-defined… More >
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