首页|Reports from Russian Academy of Sciences Add New Data to Findings in Machine Learning (Srgz: Machine Learning Methods and Properties of the Catalog of Srg/erosita Point X-ray Source Optical Counterparts In the Desi Legacy Imaging Surveys ...)
Reports from Russian Academy of Sciences Add New Data to Findings in Machine Learning (Srgz: Machine Learning Methods and Properties of the Catalog of Srg/erosita Point X-ray Source Optical Counterparts In the Desi Legacy Imaging Surveys ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Current study results on Machine Learning have been published. According to newsoriginating from Moscow, Russia, by NewsRx correspondents, research stated, “We describe the methodsof the SRGz system for the physical identification of eROSITA point X-ray sources from photometric datain the DESI Legacy Imaging Surveys footprint. We consider the models included in the SRGz system(version 2.1) that have allowed us to obtain accurate measurements of the cosmological redshift andclass of an X-ray object (quasar/galaxy/star) from multiwavelength photometric sky surveys (DESI LIS, SDSS, Pan-STARRS, WISE, eROSITA) for 87% of the entire eastern extragalactic region (0(degrees) <l<180(degrees), |b| >20 degrees).”
MoscowRussiaCyborgsEmerging TechnologiesMachine LearningRussian Academy of Sciences
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