首页|Findings on Machine Learning Discussed by Investigators at Indian Institute of Astrophysics (Possibilities of Identifying Members From Milky Way Satellite Galaxies Using Unsupervised Machine Learning Algorithms)
Findings on Machine Learning Discussed by Investigators at Indian Institute of Astrophysics (Possibilities of Identifying Members From Milky Way Satellite Galaxies Using Unsupervised Machine Learning Algorithms)
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NETL
NSTL
Indian Acad Sciences
Research findings on Machine Learning are discussed in a new report. According to news originating from Bangalore, India, by NewsRx correspondents, research stated, "A detailed study of stellar populations in Milky Way (MW) satellite galaxies remains an observational challenge due to their faintness and fewer spectroscopically confirmedmember stars. We use unsupervised machine learning methods to identify new members for nine nearby MW satellite galaxies using Gaia data release-3 (Gaia DR3) astrometry, the Dark Energy Survey (DES) and the DECam Local Volume Exploration Survey (DELVE) photometry."
BangaloreIndiaAsiaAlgorithmsCyborgsEmerging TechnologiesMachine LearningIndian Institute of Astrophysics
NETL
NSTL
Indian Acad Sciences
