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A deep learning approach to test the small-scale galaxy mor..:
Zanisi, Lorenzo
;
Huertas-Company, Marc
;
Lanusse, François
...
Monthly Notices of the Royal Astronomical Society. 501 (2020) 3 - p. 4359-4382 , 2020
Link:
https://doi.org/10.1093/mnras/staa3864
RT Journal T1 <Title>A deep learning approach to test the small-scale galaxy morphology and its relationship with star formation activity in hydrodynamical simulations</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1093_mnras_staa3864&Exemplar=1&LAN=DE A1 Zanisi, Lorenzo A1 Huertas-Company, Marc A1 Lanusse, François A1 Bottrell, Connor A1 Pillepich, Annalisa A1 Nelson, Dylan A1 Rodriguez-Gomez, Vicente A1 Shankar, Francesco A1 Hernquist, Lars A1 Dekel, Avishai A1 Margalef-Bentabol, Berta A1 Vogelsberger, Mark A1 Primack, Joel PB Oxford University Press (OUP) YR 2020 SN 0035-8711 SN 1365-2966 JF Monthly Notices of the Royal Astronomical Society VO 501 IS 3 SP 4359 OP 4382 LK http://dx.doi.org/https://doi.org/10.1093/mnras/staa3864 DO https://doi.org/10.1093/mnras/staa3864 SF ELIB - SuUB Bremen
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