347 citations · 781 across the 21 of their papers we have counts for
21 papers
Photometric redshift estimation of galaxies in the DESI Legacy Imaging Surveys
Changhua Li, Yanxia Zhang, Chenzhou Cui +14
The accurate estimation of photometric redshifts plays a crucial role in accomplishing science objectives of the large survey projects. The template-fitting and machine learning ar…
Photometric Redshift Estimation of BASS DR3 Quasars by Machine Learning
Changhua Li, Yanxia Zhang, Chenzhou Cui +9
Correlating BASS DR3 catalogue with ALLWISE database, the data from optical and infrared information are obtained. The quasars from SDSS are taken as training and test samples whil…
Identification of BASS DR3 Sources as Stars, Galaxies and Quasars by XGBoost
Changhua Li, Yanxia Zhang, Chenzhou Cui +11
The Beijing-Arizona Sky Survey (BASS) Data Release 3 (DR3) catalogue was released in 2019, which contains the data from all BASS and the Mosaic z-band Legacy Survey (MzLS) observat…
Classification of 4XMM-DR9 Sources by Machine Learning
Yanxia Zhang, Yongheng Zhao, Xue-Bing Wu
The ESA's X-ray Multi-Mirror Mission (XMM-Newton) created a new, high quality version of the XMM-Newton serendipitous source catalogue, 4XMM-DR9, which provides a wealth of informa…
A New Strategy for Estimating Photometric Redshifts of Quasars
Yanxia Zhang, Jingyi Zhang, Xin Jin +1
Based on the SDSS and SDSS-WISE quasar datasets, we put forward two schemes to estimate the photometric redshifts of quasars. Our schemes are based on the idea that the samples are…
Efficient Selection of Quasar Candidates Based on Optical and Infrared Photometric Data Using Machine Learning
Xin Jin, Yanxia Zhang, Jingyi Zhang +3
We aim to select quasar candidates based on the two large survey databases, Pan-STARRS and AllWISE. Exploring the distribution of quasars and stars in the color spaces, we find tha…