Source: AgriEngineering. Unidades: FZEA, ESALQ
Subjects: APRENDIZADO COMPUTACIONAL, DIAGNOSE FOLIAR, FERTILIZANTES NITROGENADOS, MILHO, NITROGÊNIO, NUTRIÇÃO VEGETAL, PROCESSAMENTO DE IMAGENS, REDES NEURAIS
ABNT
SILVA, Thiago Lima da et al. Machine learning in the classification of RGB images of maize (Zea mays L.) using texture attributes and different doses of nitrogen. AgriEngineering, v. 7, p. 1-22, 2025Tradução . . Disponível em: https://doi.org/10.3390/agriengineering7100317. Acesso em: 28 nov. 2025.APA
Silva, T. L. da, Devechio, F. de F. da S., Tavares, M. S., Regazzo, J. R., Sardinha, E. J. de S., Altão, L. M. R., et al. (2025). Machine learning in the classification of RGB images of maize (Zea mays L.) using texture attributes and different doses of nitrogen. AgriEngineering, 7, 1-22. doi:10.3390/agriengineering7100317NLM
Silva TL da, Devechio F de F da S, Tavares MS, Regazzo JR, Sardinha EJ de S, Altão LMR, Oliveira GP de CN, Tech ARB, Baesso MM. Machine learning in the classification of RGB images of maize (Zea mays L.) using texture attributes and different doses of nitrogen [Internet]. AgriEngineering. 2025 ; 7 1-22.[citado 2025 nov. 28 ] Available from: https://doi.org/10.3390/agriengineering7100317Vancouver
Silva TL da, Devechio F de F da S, Tavares MS, Regazzo JR, Sardinha EJ de S, Altão LMR, Oliveira GP de CN, Tech ARB, Baesso MM. Machine learning in the classification of RGB images of maize (Zea mays L.) using texture attributes and different doses of nitrogen [Internet]. AgriEngineering. 2025 ; 7 1-22.[citado 2025 nov. 28 ] Available from: https://doi.org/10.3390/agriengineering7100317
