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dc.contributor.author
Gheller, Claudio
dc.contributor.author
Vazza, Franco
dc.contributor.author
Bonafede, Annalisa
dc.date.accessioned
2023-09-26T10:44:08Z
dc.date.available
2018-11-24T15:46:29Z
dc.date.available
2018-11-26T09:50:44Z
dc.date.available
2023-09-26T10:44:08Z
dc.date.issued
2018-11
dc.identifier.issn
0035-8711
dc.identifier.issn
1365-2966
dc.identifier.other
10.1093/mnras/sty2102
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/305904
dc.identifier.doi
10.3929/ethz-b-000305904
dc.description.abstract
In this paper we introduce a reliable, fully automated and fast algorithm to detect extended extragalactic radio sources (cluster of galaxies, filaments) in existing and forthcoming surveys (like LOFAR and SKA). The proposed solution is based on the adoption of a Deep Learning approach, more specifically a Convolutional Neural Network, that proved to perform outstandingly in the processing, recognition and classification of images. The challenge, in the case of radio interferometric data, is the presence of noise and the lack of a sufficiently large number of labelled images for the training. We have specifically addressed these problems and the resulting software, COSMODEEP, proved to be an accurate, efficient and effective solution for detecting very faint sources in the simulated radio images. We present the comparison with standard source finding techniques, and discuss advantages and limitations of our new approach.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Oxford University Press
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
methods: numerical
en_US
dc.subject
galaxies: clusters: general
en_US
dc.subject
intergalactic medium
en_US
dc.subject
largescale structure of Universe
en_US
dc.title
Deep learning based detection of cosmological diffuse radio sources
en_US
dc.type
Journal Article
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2018-08-03
ethz.journal.title
Monthly Notices of the Royal Astronomical Society
ethz.journal.volume
480
en_US
ethz.journal.issue
3
en_US
ethz.journal.abbreviated
Mon. Not. R. Astron. Soc.
ethz.pages.start
3749
en_US
ethz.pages.end
3761
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.notes
It was possible to publish this article open access thanks to a Swiss National Licence with the publisher.
en_US
ethz.identifier.wos
ethz.publication.place
Oxford
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2018-11-24T15:46:30Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2018-11-26T09:51:15Z
ethz.rosetta.lastUpdated
2024-02-03T04:04:34Z
ethz.rosetta.versionExported
true
ethz.COinS
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