Radio Galaxy Zoo: Unsupervised Clustering of Convolutionally Auto-encoded Radio-astronomical Images
Radio Galaxy Zoo: Unsupervised Clustering of Convolutionally Auto-encoded Radio-astronomical Images
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Publisher
Philadelphia: The Astronomical Society of the Pacific
Journal title
Language
English
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Publisher
Philadelphia: The Astronomical Society of the Pacific
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Scope and Contents
Contents
This paper demonstrates a novel and efficient unsupervised clustering method with the combination of a self-organizing map (SOM) and a convolutional autoencoder. The rapidly increasing volume of radio-astronomical data has increased demand for machine-learning methods as solutions to classification and outlier detection. Major astronomical discover...
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Full title
Radio Galaxy Zoo: Unsupervised Clustering of Convolutionally Auto-encoded Radio-astronomical Images
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Record Identifier
TN_cdi_crossref_citationtrail_10_1088_1538_3873_ab213d
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_crossref_citationtrail_10_1088_1538_3873_ab213d
Other Identifiers
ISSN
0004-6280
E-ISSN
1538-3873
DOI
10.1088/1538-3873/ab213d
