Source: Sensors. Unidade: ESALQ
Subjects: AERONAVES NÃO TRIPULADAS, APRENDIZADO COMPUTACIONAL, GADO CANCHIM, GADO NELORE, PROCESSAMENTO DE IMAGENS, REDES NEURAIS, ZOOTECNIA DE PRECISÃO
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BARBEDO, Jayme Garcia Arnal et al. Counting Cattle in UAV Images: Dealing with Clustered Animals and Animal/Background Contrast Changes. Sensors, v. 20, p. 1-14, 2020Tradução . . Disponível em: https://doi.org/10.3390/s20072126. Acesso em: 27 ago. 2024.APA
Barbedo, J. G. A., Koenigkan, L. V., Santos, P. M., & Ribeiro, A. R. B. (2020). Counting Cattle in UAV Images: Dealing with Clustered Animals and Animal/Background Contrast Changes. Sensors, 20, 1-14. doi:10.3390/s20072126NLM
Barbedo JGA, Koenigkan LV, Santos PM, Ribeiro ARB. Counting Cattle in UAV Images: Dealing with Clustered Animals and Animal/Background Contrast Changes [Internet]. Sensors. 2020 ; 20 1-14.[citado 2024 ago. 27 ] Available from: https://doi.org/10.3390/s20072126Vancouver
Barbedo JGA, Koenigkan LV, Santos PM, Ribeiro ARB. Counting Cattle in UAV Images: Dealing with Clustered Animals and Animal/Background Contrast Changes [Internet]. Sensors. 2020 ; 20 1-14.[citado 2024 ago. 27 ] Available from: https://doi.org/10.3390/s20072126
