Borzooei, Sina 
; Scabini, Leonardo ; Miranda, Gisele Helena Barboni ; Daneshgar, Saba ; Deblieck, Lukas; Bruno, Odemir Martinez ; Langhe, Piet De; Baets, Bernard De ; Nopens, Ingmar; Torfs, Elena
Source: Journal of Water Process Engineering. Unidade: IFSC
Subjects: APRENDIZADO COMPUTACIONAL, VISÃO COMPUTACIONAL, REDES NEURAIS, TRATAMENTO DE ÁGUA
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BORZOOEI, Sina et al. Evaluation of activated sludge settling characteristics from microscopy images with deep convolutional neural networks and transfer learning. Journal of Water Process Engineering, v. 64, p. 105692-1-105692-13, 2024Tradução . . Disponível em: https://doi.org/10.1016/j.jwpe.2024.105692. Acesso em: 16 nov. 2024.APA
Borzooei, S., Scabini, L., Miranda, G. H. B., Daneshgar, S., Deblieck, L., Bruno, O. M., et al. (2024). Evaluation of activated sludge settling characteristics from microscopy images with deep convolutional neural networks and transfer learning. Journal of Water Process Engineering, 64, 105692-1-105692-13. doi:10.1016/j.jwpe.2024.105692NLM
Borzooei S, Scabini L, Miranda GHB, Daneshgar S, Deblieck L, Bruno OM, Langhe PD, Baets BD, Nopens I, Torfs E. Evaluation of activated sludge settling characteristics from microscopy images with deep convolutional neural networks and transfer learning [Internet]. Journal of Water Process Engineering. 2024 ; 64 105692-1-105692-13.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1016/j.jwpe.2024.105692Vancouver
Borzooei S, Scabini L, Miranda GHB, Daneshgar S, Deblieck L, Bruno OM, Langhe PD, Baets BD, Nopens I, Torfs E. Evaluation of activated sludge settling characteristics from microscopy images with deep convolutional neural networks and transfer learning [Internet]. Journal of Water Process Engineering. 2024 ; 64 105692-1-105692-13.[citado 2024 nov. 16 ] Available from: https://doi.org/10.1016/j.jwpe.2024.105692
