AutoSourceID-Classifier. Star-Galaxy Classification using a Convolutional Neural Network with Spatia...
AutoSourceID-Classifier. Star-Galaxy Classification using a Convolutional Neural Network with Spatial Information
About this item
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Author / Creator
Stoppa, F , Bhattacharyya, S , Ruiz de Austri, R , Vreeswijk, P , Caron, S , Zaharijas, G , Bloemen, S , Principe, G , Malyshev, D , Vodeb, V , Groot, P J , Cator, E and Nelemans, G
Publisher
Ithaca: Cornell University Library, arXiv.org
Journal title
Language
English
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Publication information
Publisher
Ithaca: Cornell University Library, arXiv.org
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Scope and Contents
Contents
Aims. Traditional star-galaxy classification techniques often rely on feature estimation from catalogues, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification's reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and f...
Alternative Titles
Full title
AutoSourceID-Classifier. Star-Galaxy Classification using a Convolutional Neural Network with Spatial Information
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Record Identifier
TN_cdi_proquest_journals_2843254770
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2843254770
Other Identifiers
E-ISSN
2331-8422
DOI
10.48550/arxiv.2307.14456
