Jianglong, Yan 
; Tetila, Everton Castelão ; Liang, Zhao ; Gonçalves, Rian Carrasco ; Castanheiro, Letícia Ferrari ; Valem, Lucas Pascotti ; Barbedo, Jayme Garcia Arnal
Source: Computers and Electronics in Agriculture. Unidades: FFCLRP, ICMC
Subjects: APRENDIZAGEM PROFUNDA, VISÃO COMPUTACIONAL, AERONAVES NÃO TRIPULADAS, PECUÁRIA DE CORTE, ZOOTECNIA DE PRECISÃO
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JIANGLONG, Yan et al. Deep learning-based UAV framework for automated morphological and growth analysis of feedlot cattle. Computers and Electronics in Agriculture, v. 245, p. 1-15, 2026Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2026.111559. Acesso em: 03 maio 2026.APA
Jianglong, Y., Tetila, E. C., Liang, Z., Gonçalves, R. C., Castanheiro, L. F., Valem, L. P., & Barbedo, J. G. A. (2026). Deep learning-based UAV framework for automated morphological and growth analysis of feedlot cattle. Computers and Electronics in Agriculture, 245, 1-15. doi:10.1016/j.compag.2026.111559NLM
Jianglong Y, Tetila EC, Liang Z, Gonçalves RC, Castanheiro LF, Valem LP, Barbedo JGA. Deep learning-based UAV framework for automated morphological and growth analysis of feedlot cattle [Internet]. Computers and Electronics in Agriculture. 2026 ; 245 1-15.[citado 2026 maio 03 ] Available from: https://doi.org/10.1016/j.compag.2026.111559Vancouver
Jianglong Y, Tetila EC, Liang Z, Gonçalves RC, Castanheiro LF, Valem LP, Barbedo JGA. Deep learning-based UAV framework for automated morphological and growth analysis of feedlot cattle [Internet]. Computers and Electronics in Agriculture. 2026 ; 245 1-15.[citado 2026 maio 03 ] Available from: https://doi.org/10.1016/j.compag.2026.111559
