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Filtros : "APRENDIZADO COMPUTACIONAL" "RESERVATÓRIOS" Removido: "Agropecuária Limpar

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  • Artigo de periodico

    Man-made object segmentation around reservoirs by an end-to-end two-phase deep learning-based workflow (2024)

    Hamidishad, Nayereh ; César Júnior, Roberto Marcondes

    Source: Journal of Applied Remote Sensing. Unidades: IME, EP

    Subjects: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, RESERVATÓRIOS

    Versão PublicadaAcesso à fonteDOIHow to cite
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    • ABNT

      HAMIDISHAD, Nayereh e CÉSAR JÚNIOR, Roberto Marcondes. Man-made object segmentation around reservoirs by an end-to-end two-phase deep learning-based workflow. Journal of Applied Remote Sensing, v. 18, n. artigo 018502, p. 1-20, 2024Tradução . . Disponível em: https://doi.org/10.1117/1.JRS.18.018502. Acesso em: 06 nov. 2024.

    • APA

      Hamidishad, N., & César Júnior, R. M. (2024). Man-made object segmentation around reservoirs by an end-to-end two-phase deep learning-based workflow. Journal of Applied Remote Sensing, 18( artigo 018502), 1-20. doi:10.1117/1.JRS.18.018502

    • NLM

      Hamidishad N, César Júnior RM. Man-made object segmentation around reservoirs by an end-to-end two-phase deep learning-based workflow [Internet]. Journal of Applied Remote Sensing. 2024 ; 18( artigo 018502): 1-20.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1117/1.JRS.18.018502

    • Vancouver

      Hamidishad N, César Júnior RM. Man-made object segmentation around reservoirs by an end-to-end two-phase deep learning-based workflow [Internet]. Journal of Applied Remote Sensing. 2024 ; 18( artigo 018502): 1-20.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1117/1.JRS.18.018502

  • Artigo de periodico

    Hybrid Machine Learning for Modeling the Relative Permeability Changes in Carbonate Reservoirs under Engineered Water Injection (2023)

    Reginato, Leonardo Fonseca; Gioria, Rafael dos Santos ; Pinto, Marcio Augusto Sampaio

    Source: Energies. Unidade: EP

    Subjects: PERMEABILIDADE DO SOLO, RESERVATÓRIOS, APRENDIZADO COMPUTACIONAL

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      REGINATO, Leonardo Fonseca e GIORIA, Rafael dos Santos e PINTO, Marcio Augusto Sampaio. Hybrid Machine Learning for Modeling the Relative Permeability Changes in Carbonate Reservoirs under Engineered Water Injection. Energies, v. 16, n. 13, 2023Tradução . . Disponível em: https://doi.org/10.3390/en16134849. Acesso em: 06 nov. 2024.

    • APA

      Reginato, L. F., Gioria, R. dos S., & Pinto, M. A. S. (2023). Hybrid Machine Learning for Modeling the Relative Permeability Changes in Carbonate Reservoirs under Engineered Water Injection. Energies, 16( 13). doi:10.3390/en16134849

    • NLM

      Reginato LF, Gioria R dos S, Pinto MAS. Hybrid Machine Learning for Modeling the Relative Permeability Changes in Carbonate Reservoirs under Engineered Water Injection [Internet]. Energies. 2023 ;16( 13):[citado 2024 nov. 06 ] Available from: https://doi.org/10.3390/en16134849

    • Vancouver

      Reginato LF, Gioria R dos S, Pinto MAS. Hybrid Machine Learning for Modeling the Relative Permeability Changes in Carbonate Reservoirs under Engineered Water Injection [Internet]. Energies. 2023 ;16( 13):[citado 2024 nov. 06 ] Available from: https://doi.org/10.3390/en16134849

  • Tese (Doutorado)

    Two-phase methods to segment man-made objects around reservoirs (2023)

    Hamidishad, Nayereh; César Júnior, Roberto Marcondes (Orientador)

    Unidade: IME

    Subjects: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, RESERVATÓRIOS

    Acesso à fonteAcesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      HAMIDISHAD, Nayereh. Two-phase methods to segment man-made objects around reservoirs. 2023. Tese (Doutorado) – Universidade de São Paulo, São Paulo, 2023. Disponível em: https://www.teses.usp.br/teses/disponiveis/45/45134/tde-05062023-071021/. Acesso em: 06 nov. 2024.

    • APA

      Hamidishad, N. (2023). Two-phase methods to segment man-made objects around reservoirs (Tese (Doutorado). Universidade de São Paulo, São Paulo. Recuperado de https://www.teses.usp.br/teses/disponiveis/45/45134/tde-05062023-071021/

    • NLM

      Hamidishad N. Two-phase methods to segment man-made objects around reservoirs [Internet]. 2023 ;[citado 2024 nov. 06 ] Available from: https://www.teses.usp.br/teses/disponiveis/45/45134/tde-05062023-071021/

    • Vancouver

      Hamidishad N. Two-phase methods to segment man-made objects around reservoirs [Internet]. 2023 ;[citado 2024 nov. 06 ] Available from: https://www.teses.usp.br/teses/disponiveis/45/45134/tde-05062023-071021/

  • Dissertação (Mestrado)

    Application of machine learning techniques for modeling of relative permeability in engineered water injection in carbonate reservoirs (2022)

    Reginato, Leonardo Fonseca; Pinto, Marcio Augusto Sampaio (Orientador)

    Unidade: EP

    Subjects: CARBONATOS, RESERVATÓRIOS, APRENDIZADO COMPUTACIONAL, INJEÇÃO (ENGENHARIA)

    Acesso à fonteHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas

    • ABNT

      REGINATO, Leonardo Fonseca. Application of machine learning techniques for modeling of relative permeability in engineered water injection in carbonate reservoirs. 2022. Dissertação (Mestrado) – Universidade de São Paulo, São Paulo, 2022. Disponível em: https://www.teses.usp.br/teses/disponiveis/3/3134/tde-26082022-083727/. Acesso em: 06 nov. 2024.

    • APA

      Reginato, L. F. (2022). Application of machine learning techniques for modeling of relative permeability in engineered water injection in carbonate reservoirs (Dissertação (Mestrado). Universidade de São Paulo, São Paulo. Recuperado de https://www.teses.usp.br/teses/disponiveis/3/3134/tde-26082022-083727/

    • NLM

      Reginato LF. Application of machine learning techniques for modeling of relative permeability in engineered water injection in carbonate reservoirs [Internet]. 2022 ;[citado 2024 nov. 06 ] Available from: https://www.teses.usp.br/teses/disponiveis/3/3134/tde-26082022-083727/

    • Vancouver

      Reginato LF. Application of machine learning techniques for modeling of relative permeability in engineered water injection in carbonate reservoirs [Internet]. 2022 ;[citado 2024 nov. 06 ] Available from: https://www.teses.usp.br/teses/disponiveis/3/3134/tde-26082022-083727/
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