Sugarcane Yield Mapping Using High-Resolution Imagery Data and Machine Learning Technique (2021)
Source: Remote Sensing. Unidade: ESALQ
Subjects: AGRICULTURA DE PRECISÃO, APRENDIZADO COMPUTACIONAL, CANA-DE-AÇÚCAR, IMAGEAMENTO DE SATÉLITE, SENSORIAMENTO REMOTO
ABNT
CANATA, Tatiana Fernanda et al. Sugarcane Yield Mapping Using High-Resolution Imagery Data and Machine Learning Technique. Remote Sensing, v. 13, p. 1-14, 2021Tradução . . Disponível em: https://doi.org/10.3390/rs13020232. Acesso em: 16 nov. 2024.APA
Canata, T. F., Wei, M. C. F., Maldaner, L. F., & Molin, J. P. (2021). Sugarcane Yield Mapping Using High-Resolution Imagery Data and Machine Learning Technique. Remote Sensing, 13, 1-14. doi:10.3390/rs13020232NLM
Canata TF, Wei MCF, Maldaner LF, Molin JP. Sugarcane Yield Mapping Using High-Resolution Imagery Data and Machine Learning Technique [Internet]. Remote Sensing. 2021 ; 13 1-14.[citado 2024 nov. 16 ] Available from: https://doi.org/10.3390/rs13020232Vancouver
Canata TF, Wei MCF, Maldaner LF, Molin JP. Sugarcane Yield Mapping Using High-Resolution Imagery Data and Machine Learning Technique [Internet]. Remote Sensing. 2021 ; 13 1-14.[citado 2024 nov. 16 ] Available from: https://doi.org/10.3390/rs13020232