Source: Remote Sensing. Unidades: ESALQ, IEE, IGC
Subjects: AEROFOTOGRAMETRIA, AERONAVES NÃO TRIPULADAS, APRENDIZADO COMPUTACIONAL, ÁRVORES FLORESTAIS, DOSSEL (BOTÂNICA), ECOLOGIA DA RESTAURAÇÃO, HETEROGENEIDADE
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ALBUQUERQUE, Rafael Walter et al. Mapping key indicators of forest restoration in the Amazon using a low-cost drone and artificial intelligence. Remote Sensing, v. 14, p. 1-28, 2022Tradução . . Disponível em: https://doi.org/10.3390/rs14040830. Acesso em: 22 dez. 2024.APA
Albuquerque, R. W., Vieira, D. L. M., Ferreira, M. E., Soares, L. P., Olsen, S. I., Araujo, L. S., et al. (2022). Mapping key indicators of forest restoration in the Amazon using a low-cost drone and artificial intelligence. Remote Sensing, 14, 1-28. doi:10.3390/rs14040830NLM
Albuquerque RW, Vieira DLM, Ferreira ME, Soares LP, Olsen SI, Araujo LS, Vicente LE, Tymus JRC, Balieiro CP, Matsumoto MH, Grohmann CH. Mapping key indicators of forest restoration in the Amazon using a low-cost drone and artificial intelligence [Internet]. Remote Sensing. 2022 ; 14 1-28.[citado 2024 dez. 22 ] Available from: https://doi.org/10.3390/rs14040830Vancouver
Albuquerque RW, Vieira DLM, Ferreira ME, Soares LP, Olsen SI, Araujo LS, Vicente LE, Tymus JRC, Balieiro CP, Matsumoto MH, Grohmann CH. Mapping key indicators of forest restoration in the Amazon using a low-cost drone and artificial intelligence [Internet]. Remote Sensing. 2022 ; 14 1-28.[citado 2024 dez. 22 ] Available from: https://doi.org/10.3390/rs14040830