Condori, Rayner Harold Montes; Bruno, Odemir Martinez 
; Romualdo, Liliane Maria; Luz, Pedro Henrique de Cerqueira
Source: Proceedings. Conference titles: Workshop of Computer Vision - WCV. Unidades: IFSC, FZEA
Subjects: TEXTURA, AVALIAÇÃO NUTRICIONAL, MILHO
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ABNT
CONDORI, Rayner Harold Montes et al. Comparison between traditional texture methods and deep learning descriptors for detection of nitrogen deficiency in maize crops. 2017, Anais.. Piscataway: Institute of Electrical and Electronics Engineers - IEEE - Computer Society, 2017. Disponível em: https://doi.org/10.1109/WVC.2017.00009. Acesso em: 05 out. 2024.APA
Condori, R. H. M., Bruno, O. M., Romualdo, L. M., & Luz, P. H. de C. (2017). Comparison between traditional texture methods and deep learning descriptors for detection of nitrogen deficiency in maize crops. In Proceedings. Piscataway: Institute of Electrical and Electronics Engineers - IEEE - Computer Society. doi:10.1109/WVC.2017.00009NLM
Condori RHM, Bruno OM, Romualdo LM, Luz PH de C. Comparison between traditional texture methods and deep learning descriptors for detection of nitrogen deficiency in maize crops [Internet]. Proceedings. 2017 ;[citado 2024 out. 05 ] Available from: https://doi.org/10.1109/WVC.2017.00009Vancouver
Condori RHM, Bruno OM, Romualdo LM, Luz PH de C. Comparison between traditional texture methods and deep learning descriptors for detection of nitrogen deficiency in maize crops [Internet]. Proceedings. 2017 ;[citado 2024 out. 05 ] Available from: https://doi.org/10.1109/WVC.2017.00009
