Classification of sugarcane areas in Landsat images using machine learning algorithms (2024)
Source: Brazilian Journal of Biometrics. Unidade: ESALQ
Subjects: ALGORITMOS, APRENDIZADO COMPUTACIONAL, CANA-DE-AÇÚCAR, COBERTURA DO SOLO, IMAGEAMENTO DE SATÉLITE, MAPEAMENTO DO SOLO, SENSORIAMENTO REMOTO
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BARROS, Ana Clara Arantes Villas Bôas de et al. Classification of sugarcane areas in Landsat images using machine learning algorithms. Brazilian Journal of Biometrics, v. 42, p. 147–157, 2024Tradução . . Disponível em: https://doi.org/10.28951/bjb.v42i2.693. Acesso em: 01 out. 2024.APA
Barros, A. C. A. V. B. de, Silva, M. A., Marques, R. D., Lobos, C. M. V., & Luciano, A. C. dos S. (2024). Classification of sugarcane areas in Landsat images using machine learning algorithms. Brazilian Journal of Biometrics, 42, 147–157. doi:10.28951/bjb.v42i2.693NLM
Barros ACAVB de, Silva MA, Marques RD, Lobos CMV, Luciano AC dos S. Classification of sugarcane areas in Landsat images using machine learning algorithms [Internet]. Brazilian Journal of Biometrics. 2024 ; 42 147–157.[citado 2024 out. 01 ] Available from: https://doi.org/10.28951/bjb.v42i2.693Vancouver
Barros ACAVB de, Silva MA, Marques RD, Lobos CMV, Luciano AC dos S. Classification of sugarcane areas in Landsat images using machine learning algorithms [Internet]. Brazilian Journal of Biometrics. 2024 ; 42 147–157.[citado 2024 out. 01 ] Available from: https://doi.org/10.28951/bjb.v42i2.693