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Found 4 papers, 2 papers with code
Photometric selection and redshifts for quasars in the Kilo-Degree Survey Data Release 4
We find that XGB is the most robust model for classification, while ANN performs the best for combined classification and redshift.
Cosmology and Nongalactic Astrophysics
Catalog of quasars from the Kilo-Degree Survey Data Release 3
Our study presents the first comprehensive quasar selection from deep high-quality KiDS data and will serve as the basis for versatile studies of the QSO population detected by this survey.
Testing Convolutional Neural Networks for finding strong gravitational lenses in KiDS
We have tested the ConvNet lens-finders on a sample of 21789 Luminous Red Galaxies (LRGs) selected from KiDS and we have analyzed and compared the results with our previous ConvNet lens-finder on the same sample.
Astrophysics of Galaxies Instrumentation and Methods for Astrophysics
Finding Strong Gravitational Lenses in the Kilo Degree Survey with Convolutional Neural Networks
The volume of data that will be produced by new-generation surveys requires automatic classification methods to select and analyze sources.
Astrophysics of Galaxies
