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  • Artigo de periodico

    Self-excited primary and secondary instability of laminar separation bubbles (2021)

    Rodriguez, Daniel ; Gennaro, Elmer Mateus ; Souza, Leandro Franco de

    Source: Journal of Fluid Mechanics. Unidade: ICMC

    Subjects: MECÂNICA DOS FLUÍDOS, ONDAS DE KELVIN

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    • ABNT

      RODRIGUEZ, Daniel e GENNARO, Elmer Mateus e SOUZA, Leandro Franco de. Self-excited primary and secondary instability of laminar separation bubbles. Journal of Fluid Mechanics, v. 906, p. A13-1-A13-34, 2021Tradução . . Disponível em: https://doi.org/10.1017/jfm.2020.767. Acesso em: 17 jul. 2024.

    • APA

      Rodriguez, D., Gennaro, E. M., & Souza, L. F. de. (2021). Self-excited primary and secondary instability of laminar separation bubbles. Journal of Fluid Mechanics, 906, A13-1-A13-34. doi:10.1017/jfm.2020.767

    • NLM

      Rodriguez D, Gennaro EM, Souza LF de. Self-excited primary and secondary instability of laminar separation bubbles [Internet]. Journal of Fluid Mechanics. 2021 ; 906 A13-1-A13-34.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1017/jfm.2020.767

    • Vancouver

      Rodriguez D, Gennaro EM, Souza LF de. Self-excited primary and secondary instability of laminar separation bubbles [Internet]. Journal of Fluid Mechanics. 2021 ; 906 A13-1-A13-34.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1017/jfm.2020.767

  • Artigo de periodico

    A superpixel-driven deep learning approach for the analysis of dermatological wounds (2020)

    Blanco, Gustavo; Traina, Agma Juci Machado ; Traina Junior, Caetano ; Azevedo-Marques, Paulo Mazzoncini de ; Jorge, Ana Elisa Serafim ; Oliveira, Daniel de; Bêdo, Marcos Vinícius Naves

    Source: Computer Methods and Programs in Biomedicine. Unidades: ICMC, FMRP

    Subjects: PROCESSAMENTO DE IMAGENS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, ÚLCERA CUTÂNEA

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    • ABNT

      BLANCO, Gustavo et al. A superpixel-driven deep learning approach for the analysis of dermatological wounds. Computer Methods and Programs in Biomedicine, v. 183, n. Ja 2020, p. 1-9, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.cmpb.2019.105079. Acesso em: 17 jul. 2024.

    • APA

      Blanco, G., Traina, A. J. M., Traina Junior, C., Azevedo-Marques, P. M. de, Jorge, A. E. S., Oliveira, D. de, & Bêdo, M. V. N. (2020). A superpixel-driven deep learning approach for the analysis of dermatological wounds. Computer Methods and Programs in Biomedicine, 183( Ja 2020), 1-9. doi:10.1016/j.cmpb.2019.105079

    • NLM

      Blanco G, Traina AJM, Traina Junior C, Azevedo-Marques PM de, Jorge AES, Oliveira D de, Bêdo MVN. A superpixel-driven deep learning approach for the analysis of dermatological wounds [Internet]. Computer Methods and Programs in Biomedicine. 2020 ; 183( Ja 2020): 1-9.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1016/j.cmpb.2019.105079

    • Vancouver

      Blanco G, Traina AJM, Traina Junior C, Azevedo-Marques PM de, Jorge AES, Oliveira D de, Bêdo MVN. A superpixel-driven deep learning approach for the analysis of dermatological wounds [Internet]. Computer Methods and Programs in Biomedicine. 2020 ; 183( Ja 2020): 1-9.[citado 2024 jul. 17 ] Available from: https://doi.org/10.1016/j.cmpb.2019.105079
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