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  4. FIRST radio galaxy data set containing curated labels of classes FRI, FRII, compact and bent
 
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FIRST radio galaxy data set containing curated labels of classes FRI, FRII, compact and bent

Citation Link: https://doi.org/10.15480/882.5011
Publikationstyp
Data Paper
Date Issued
2023-02-11
Sprache
English
Author(s)
Griese, Florian  orcid-logo
Kummer, Janis  
Connor, Patrick L.S.  
Brüggen, Marcus  
Rustige, Lennart  
Institut
Biomedizinische Bildgebung E-5  
TORE-DOI
10.15480/882.5011
TORE-URI
http://hdl.handle.net/11420/15027
Journal
Data in Brief  
Volume
47
Article Number
108974
Citation
Data in Brief 47: 108974 (2023-04-01)
Publisher DOI
10.1016/j.dib.2023.108974
Scopus ID
2-s2.0-85148332698
Publisher
Elsevier
Automated classification of astronomical sources is often challenging due to the scarcity of labelled training data. We present a data set with a total number of 2158 data items that contains radio galaxy images with their corresponding morphological labels taken from various catalogues [1,2]. The data set is curated by removing duplicates, ambiguous morphological labels and by different meta data formats. The image data was acquired by the VLA FIRST (Faint Images of the Radio Sky at Twenty-Centimeters) survey [3]. The morphological labels are collected and the catalogue specific classification definition is converted into a 4-class classification scheme: FRI, FRII, Compact and Bent sources. FRI and FRII correspond to the two classes of the widely used Faranoff-Riley classification [4]. We consider two more classes: compact sources and bent-tail galaxies. For duplicates with different morphological labels, the galaxy is regarded as ambiguously labeled and both coordinates are removed. For the remaining list of coordinates, the radio galaxy images are collected from the virtual observatory skyview (https://skyview.gsfc.nasa.gov/current/cgi/query.pl). The gray value images are provided in the size of 300 × 300 pixel and all pixels with a value below three times the local RMS of the noise are set to this threshold value. The data set is useful for the development of robust machine learning models that automate the classification of radio galaxy images.
Subjects
Bent
Compact
Fanaroff-Riley
FIRST survey
FRI
FRII
Radio Galaxy
DDC Class
530: Physik
600: Technik
Funding(s)
Center for Data and Computing in Natural Sciences  
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by/4.0/
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