Context. The two currently largest all-sky photometric datasets, WISE and SuperCOSMOS, have been recently cross-matched to construct a novel photometric redshift catalogue on 70% of the sky. Galaxies were separated from stars and quasars through colour cuts, which may leave imperfections because different source types may overlap in colour space. Aims. The aim of the present work is to identify galaxies in the WISE × SuperCOSMOS catalogue through an alternative approach of machine learning. This allows us to define more complex separations in the multi-colour space than is possible with simple colour cuts, and should provide a more reliable source classification. Methods. For the automatised classification we used the suppor...
In this paper, we discuss an application of machine-learning-based methods to the identification of ...
Aims. The aim of this work is to develop a comprehensive method for classifying sources in large sky...
Aims.The aim of this work is to develop a comprehensive method for classifying sources in large sky ...
Context. The two currently largest all-sky photometric datasets, WISE and SuperCOSMOS, have been rec...
This is version 1, you should use the updated version 2 that was accepted for publication: 10.5281/z...
We used 3.1 million spectroscopically labelled sources from the Sloan Digital Sky Survey (SDSS) to t...
Context. Machine learning methods are effective tools in astronomical tasks for classifying objects ...
The Paper: https://arxiv.org/abs/1909.10963 Abstract: We used 3.1 million spectroscopically labelle...
This is the same as the published data available under 10.5281/zenodo.3768398, but in the format of ...
This study involves two photometric catalogues, AllWISE and Pan-STARRS Data Release 1, which were cr...
Aims. The aim of this work is to develop a comprehensive method for classifying sources in large sky...
Aims. The aim of this work is to develop a comprehensive method for classifying sources in large sky...
In this paper, we discuss an application of machine-learning-based methods to the identification of ...
Aims. The aim of this work is to develop a comprehensive method for classifying sources in large sky...
In this paper, we discuss an application of machine-learning-based methods to the identification of ...
In this paper, we discuss an application of machine-learning-based methods to the identification of ...
Aims. The aim of this work is to develop a comprehensive method for classifying sources in large sky...
Aims.The aim of this work is to develop a comprehensive method for classifying sources in large sky ...
Context. The two currently largest all-sky photometric datasets, WISE and SuperCOSMOS, have been rec...
This is version 1, you should use the updated version 2 that was accepted for publication: 10.5281/z...
We used 3.1 million spectroscopically labelled sources from the Sloan Digital Sky Survey (SDSS) to t...
Context. Machine learning methods are effective tools in astronomical tasks for classifying objects ...
The Paper: https://arxiv.org/abs/1909.10963 Abstract: We used 3.1 million spectroscopically labelle...
This is the same as the published data available under 10.5281/zenodo.3768398, but in the format of ...
This study involves two photometric catalogues, AllWISE and Pan-STARRS Data Release 1, which were cr...
Aims. The aim of this work is to develop a comprehensive method for classifying sources in large sky...
Aims. The aim of this work is to develop a comprehensive method for classifying sources in large sky...
In this paper, we discuss an application of machine-learning-based methods to the identification of ...
Aims. The aim of this work is to develop a comprehensive method for classifying sources in large sky...
In this paper, we discuss an application of machine-learning-based methods to the identification of ...
In this paper, we discuss an application of machine-learning-based methods to the identification of ...
Aims. The aim of this work is to develop a comprehensive method for classifying sources in large sky...
Aims.The aim of this work is to develop a comprehensive method for classifying sources in large sky ...