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Filtros : "Workshop of Computer Vision - WCV" Limpar

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Trabalho de evento
Alignment, scale and skew correction for optical mark recognition documents based (2019)
Elias, Erik Miguel de ; Tasinaffo, Paulo Marcelo ; Hirata Júnior, Roberto
Source: Proceedings. Conference titles: Workshop of Computer Vision - WCV. Unidade: IME
Assunto: PROCESSAMENTO DE IMAGENS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ELIAS, Erik Miguel de e TASINAFFO, Paulo Marcelo e HIRATA JÚNIOR, Roberto. Alignment, scale and skew correction for optical mark recognition documents based. 2019, Anais.. Piscataway: IEEE, 2019. Disponível em: https://doi.org/10.1109/WVC.2019.8876933. Acesso em: 14 nov. 2025.
APA
Elias, E. M. de, Tasinaffo, P. M., & Hirata Júnior, R. (2019). Alignment, scale and skew correction for optical mark recognition documents based. In Proceedings. Piscataway: IEEE. doi:10.1109/WVC.2019.8876933
NLM
Elias EM de, Tasinaffo PM, Hirata Júnior R. Alignment, scale and skew correction for optical mark recognition documents based [Internet]. Proceedings. 2019 ;[citado 2025 nov. 14 ] Available from: https://doi.org/10.1109/WVC.2019.8876933
Vancouver
Elias EM de, Tasinaffo PM, Hirata Júnior R. Alignment, scale and skew correction for optical mark recognition documents based [Internet]. Proceedings. 2019 ;[citado 2025 nov. 14 ] Available from: https://doi.org/10.1109/WVC.2019.8876933
Trabalho de evento
Comparison between traditional texture methods and deep learning descriptors for detection of nitrogen deficiency in maize crops (2017)
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 14 nov. 2025.
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.2017.00009
NLM
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 2025 nov. 14 ] Available from: https://doi.org/10.1109/WVC.2017.00009
Vancouver
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 2025 nov. 14 ] Available from: https://doi.org/10.1109/WVC.2017.00009

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