Deep learning for identification of water deficits in sugarcane based on thermal images (2022)
Fonte: Agricultural Water Management. Unidades: ESALQ, ICMC, CENA
Assuntos: DEFICIT HÍDRICO, APRENDIZADO COMPUTACIONAL, REDES NEURAIS, CANA-DE-AÇÚCAR
ABNT
MELO, Leonardo Leite de et al. Deep learning for identification of water deficits in sugarcane based on thermal images. Agricultural Water Management, v. 272, p. 1-13, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.agwat.2022.107820. Acesso em: 26 ago. 2024.APA
Melo, L. L. de, Melo, V. G. M. L. de, Marques, P. A. A., Frizzone, J. A., Coelho, R. D., Romero, R. A. F., & Barros, T. H. da S. (2022). Deep learning for identification of water deficits in sugarcane based on thermal images. Agricultural Water Management, 272, 1-13. doi:10.1016/j.agwat.2022.107820NLM
Melo LL de, Melo VGML de, Marques PAA, Frizzone JA, Coelho RD, Romero RAF, Barros TH da S. Deep learning for identification of water deficits in sugarcane based on thermal images [Internet]. Agricultural Water Management. 2022 ; 272 1-13.[citado 2024 ago. 26 ] Available from: https://doi.org/10.1016/j.agwat.2022.107820Vancouver
Melo LL de, Melo VGML de, Marques PAA, Frizzone JA, Coelho RD, Romero RAF, Barros TH da S. Deep learning for identification of water deficits in sugarcane based on thermal images [Internet]. Agricultural Water Management. 2022 ; 272 1-13.[citado 2024 ago. 26 ] Available from: https://doi.org/10.1016/j.agwat.2022.107820