Machicao, Jeaneth 
; Specht, Alison; Vellenich, Danton ; Meneguzzi, Leandro ; David, Romain; Stall, Shelley; Ferraz, Katia ; Mabile, Laurence; O’Brien, Margaret; Corrêa, Pedro
Source: Data Science Journal. Unidades: EP, ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, COLETA DE DADOS, IMAGEM DIGITAL, INDICADORES SOCIOECONÔMICOS, REDES NEURAIS
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MACHICAO, Jeaneth et al. A Deep-learning method for the prediction of socio-economic indicators from street-view imagery using a case study from Brazil. Data Science Journal, v. 21, n. 6, p. 1–15, 2022Tradução . . Disponível em: https://doi.org/10.5334/dsj-2022-006. Acesso em: 30 jan. 2023.APA
Machicao, J., Specht, A., Vellenich, D., Meneguzzi, L., David, R., Stall, S., et al. (2022). A Deep-learning method for the prediction of socio-economic indicators from street-view imagery using a case study from Brazil. Data Science Journal, 21( 6), 1–15. doi:10.5334/dsj-2022-006NLM
Machicao J, Specht A, Vellenich D, Meneguzzi L, David R, Stall S, Ferraz K, Mabile L, O’Brien M, Corrêa P. A Deep-learning method for the prediction of socio-economic indicators from street-view imagery using a case study from Brazil [Internet]. Data Science Journal. 2022 ; 21( 6): 1–15.[citado 2023 jan. 30 ] Available from: https://doi.org/10.5334/dsj-2022-006Vancouver
Machicao J, Specht A, Vellenich D, Meneguzzi L, David R, Stall S, Ferraz K, Mabile L, O’Brien M, Corrêa P. A Deep-learning method for the prediction of socio-economic indicators from street-view imagery using a case study from Brazil [Internet]. Data Science Journal. 2022 ; 21( 6): 1–15.[citado 2023 jan. 30 ] Available from: https://doi.org/10.5334/dsj-2022-006
