Galaxy morphological classification catalogue of the Dark Energy Survey Year 3 data with convolutional neural networks Article

Cheng, Ting-Yun, Conselice, Christopher J, Aragon-Salamanca, Alfonso et al. (2021). Galaxy morphological classification catalogue of the Dark Energy Survey Year 3 data with convolutional neural networks . MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 507(3), 4425-4444. 10.1093/mnras/stab2142

Open Access International Collaboration

cited authors

  • Cheng, Ting-Yun; Conselice, Christopher J; Aragon-Salamanca, Alfonso; Aguena, M; Allam, S; Andrade-Oliveira, F; Annis, J; Bluck, AFL; Brooks, D; Burke, DL; Kind, M Carrasco; Carretero, J; Choi, A; Costanzi, M; da Costa, LN; Pereira, MES; De Vicente, J; Diehl, HT; Drlica-Wagner, A; Eckert, K; Everett, S; Evrard, AE; Ferrero, I; Fosalba, P; Frieman, J; Garcia-Bellido, J; Gerdes, DW; Giannantonio, T; Gruen, D; Gruendl, RA; Gschwend, J; Gutierrez, G; Hinton, SR; Hollowood, DL; Honscheid, K; James, DJ; Krause, E; Kuehn, K; Kuropatkin, N; Lahav, O; Maia, MAG; March, M; Menanteau, F; Miquel, R; Morgan, R; Paz-Chinchon, F; Pieres, A; Malagon, AA Plazas; Roodman, A; Sanchez, E; Scarpine, V; Serrano, S; Sevilla-Noarbe, I; Smith, M; Soares-Santos, M; Suchyta, E; Swanson, MEC; Tarle, G; Thomas, D; To, C

authors

publication date

  • November 1, 2021

keywords

  • Astronomy & Astrophysics
  • COSMOS
  • DATA RELEASE
  • DIGITAL SKY SURVEY
  • EVOLUTION
  • FIELD
  • LUMINOSITY
  • ORIENTED GRADIENTS
  • Physical Sciences
  • SPECTRAL CLASSIFICATION
  • SUPPORT VECTOR MACHINES
  • Science & Technology
  • ZOO
  • catalogues
  • galaxies: structure
  • methods: data analysis
  • methods: observational

Digital Object Identifier (DOI)

publisher

  • OXFORD UNIV PRESS

start page

  • 4425

end page

  • 4444

volume

  • 507

issue

  • 3