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dc.contributor.author
Bom, C. R.
dc.contributor.author
Cortesi, A.
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Ribeiro, U.
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Dias, L. O.
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Kelkar, K.
dc.contributor.author
Smith Castelli, Analia Viviana
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Santana Silva, L.
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Lopes Silva, V.
dc.contributor.author
Gonçalves, T. S.
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Abramo, L. R.
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Lima, E. V. R.
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Almeida Fernandes, F.
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Espinosa, L.
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Li, L.
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Buzzo, M.L.
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Mendes de Oliveira, Claudia Lucia
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Sodré, Laerte
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Ferrari, F.
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Alvarez Candal, A.
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Grossi, M.
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Telles, E.
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Torres Flores, S.
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Werner, S. V.
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Kanaan, A.
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Ribeiro, T.
dc.contributor.author
Schoenell, W.
dc.date.available
2024-10-18T14:40:13Z
dc.date.issued
2024-03
dc.identifier.citation
Bom, C. R.; Cortesi, A.; Ribeiro, U.; Dias, L. O.; Kelkar, K.; et al.; An extended catalogue of galaxy morphology using deep learning in southern photometric local universe survey data release 3; Wiley Blackwell Publishing, Inc; Monthly Notices of the Royal Astronomical Society; 528; 3; 3-2024; 4188-4208
dc.identifier.issn
0035-8711
dc.identifier.uri
http://hdl.handle.net/11336/246130
dc.description.abstract
The morphological diversity of galaxies is a relevant probe of galaxy evolution and cosmological structure formation. However, in large sky surveys, even the morphological classification of galaxies into two classes, like late-type (LT) and early-type (ET), still represents a significant challenge. In this work, we present a Deep Learning (DL) based morphological catalogue built from images obtained by the Southern Photometric Local Universe Survey (S-PLUS) Data Release 3 (DR3). Our DL method achieves a purity rate of 98.5 per cent in accurately distinguishing between spiral, as part of the larger category of LT galaxies, and elliptical, belonging to ET galaxies. Additionally, we have implemented a secondary classifier that evaluates the quality of each galaxy stamp, which allows to select only high-quality images when studying properties of galaxies on the basis of their DL morphology. From our LT/ET catalogue of galaxies, we recover the expected colour–magnitude diagram in which LT galaxies display bluer colours than ET ones. Furthermore, we also investigate the clustering of galaxies based on their morphology, along with their relationship to the surrounding environment. As a result, we deliver a full morphological catalogue with 164 314 objects complete up to rpetro < 18, covering ∼1800 deg2, from which ∼55 000 are classified as high reliability, including a significant area of the Southern hemisphere that was not covered by previous morphology catalogues.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Wiley Blackwell Publishing, Inc
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
CATALOGUES
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GALAXIES: FUNDAMENTAL PARAMETERS
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GALAXIES: STRUCTURE
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TECHNIQUES: IMAGE PROCESSING
dc.subject.classification
Otras Ciencias Naturales y Exactas
dc.subject.classification
Otras Ciencias Naturales y Exactas
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
An extended catalogue of galaxy morphology using deep learning in southern photometric local universe survey data release 3
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2024-05-07T13:30:28Z
dc.journal.volume
528
dc.journal.number
3
dc.journal.pagination
4188-4208
dc.journal.pais
Reino Unido
dc.description.fil
Fil: Bom, C. R.. Centro Brasileiro de Pesquisas Físicas; Brasil
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Fil: Cortesi, A.. Universidade Federal do Rio de Janeiro; Brasil
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Fil: Ribeiro, U.. Centro Brasileiro de Pesquisas Físicas; Brasil
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Fil: Dias, L. O.. Centro Brasileiro de Pesquisas Físicas; Brasil
dc.description.fil
Fil: Kelkar, K.. Universidad Técnica Federico Santa María; Chile
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Fil: Smith Castelli, Analia Viviana. Universidad Nacional de La Plata; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica La Plata; Argentina
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Fil: Santana Silva, L.. Universidade Cruzeiro Do Sul; Brasil
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Fil: Lopes Silva, V.. Universidade Federal do Rio de Janeiro; Brasil
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Fil: Gonçalves, T. S.. Universidade Federal do Rio de Janeiro; Brasil
dc.description.fil
Fil: Abramo, L. R.. Universidade de Sao Paulo; Brasil
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Fil: Lima, E. V. R.. Universidade de Sao Paulo; Brasil
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Fil: Almeida Fernandes, F.. Universidade de Sao Paulo; Brasil
dc.description.fil
Fil: Espinosa, L.. Universidade de Sao Paulo; Brasil
dc.description.fil
Fil: Li, L.. Universidade de Sao Paulo; Brasil
dc.description.fil
Fil: Buzzo, M.L.. Swinburne University Of Technology; Australia
dc.description.fil
Fil: Mendes de Oliveira, Claudia Lucia. Universidade de Sao Paulo; Brasil
dc.description.fil
Fil: Sodré, Laerte. Universidade de Sao Paulo; Brasil
dc.description.fil
Fil: Ferrari, F.. Universidade Federal do Rio Grande; Brasil
dc.description.fil
Fil: Alvarez Candal, A.. Ministério de Ciencia, Tecnologia e Innovacao. Observatorio Nacional; Brasil
dc.description.fil
Fil: Grossi, M.. Universidade Federal do Rio de Janeiro; Brasil
dc.description.fil
Fil: Telles, E.. Ministério de Ciencia, Tecnologia e Innovacao. Observatorio Nacional; Brasil
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Fil: Torres Flores, S.. Universidad de La Serena; Chile
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Fil: Werner, S. V.. Science and Technology Facilities Council of Nottingham. Rutherford Appleton Laboratory; Reino Unido. University of Nottingham; Estados Unidos
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Fil: Kanaan, A.. Universidade Federal de Santa Catarina; Brasil
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Fil: Ribeiro, T.. Universidade Federal do Rio Grande do Sul; Brasil
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Fil: Schoenell, W.. National Optical Astronomy Observatory; Estados Unidos
dc.journal.title
Monthly Notices of the Royal Astronomical Society
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1093/mnras/stad3956
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/mnras/article/528/3/4188/7492270
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