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Filtros : "Financiado pela NSF" "IEEE Transactions on Visualization and Computer Graphics" Removidos: "FATORES DE RISCO" "Universidade Ibirapuera" "Eckert, Hellmut" "Livro de resumos" Limpar

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  • Artigo de periodico

    GLoG: Laplacian of Gaussian for spatial pattern detection in spatio-temporal data (2021)

    Nonato, Luis Gustavo ; Carmo, Fabiano Petronetto do ; Silva, Claudio

    Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC

    Subjects: PROCESSAMENTO DE IMAGENS, VISÃO COMPUTACIONAL, ANÁLISE DE DADOS

    PrivadoAcesso à fonteDOIHow to cite
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    • ABNT

      NONATO, Luis Gustavo e CARMO, Fabiano Petronetto do e SILVA, Claudio. GLoG: Laplacian of Gaussian for spatial pattern detection in spatio-temporal data. IEEE Transactions on Visualization and Computer Graphics, v. 27, n. 8, p. 3481-3492, 2021Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2020.2978847. Acesso em: 05 nov. 2024.

    • APA

      Nonato, L. G., Carmo, F. P. do, & Silva, C. (2021). GLoG: Laplacian of Gaussian for spatial pattern detection in spatio-temporal data. IEEE Transactions on Visualization and Computer Graphics, 27( 8), 3481-3492. doi:10.1109/TVCG.2020.2978847

    • NLM

      Nonato LG, Carmo FP do, Silva C. GLoG: Laplacian of Gaussian for spatial pattern detection in spatio-temporal data [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 8): 3481-3492.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1109/TVCG.2020.2978847

    • Vancouver

      Nonato LG, Carmo FP do, Silva C. GLoG: Laplacian of Gaussian for spatial pattern detection in spatio-temporal data [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 8): 3481-3492.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1109/TVCG.2020.2978847

  • Artigo de periodico

    TopoMap: a 0-dimensional homology preserving projection of high-dimensional data (2021)

    Doraiswamy, Harish ; Tierny, Julien ; Silva, Paulo J. S. ; Nonato, Luis Gustavo ; Silva, Claudio

    Source: IEEE Transactions on Visualization and Computer Graphics. Unidade: ICMC

    Subjects: TOPOLOGIA, ANÁLISE DE DADOS, PROJEÇÃO

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

    • ABNT

      DORAISWAMY, Harish et al. TopoMap: a 0-dimensional homology preserving projection of high-dimensional data. IEEE Transactions on Visualization and Computer Graphics, v. 27, n. 2, p. 561-571, 2021Tradução . . Disponível em: https://doi.org/10.1109/TVCG.2020.3030441. Acesso em: 05 nov. 2024.

    • APA

      Doraiswamy, H., Tierny, J., Silva, P. J. S., Nonato, L. G., & Silva, C. (2021). TopoMap: a 0-dimensional homology preserving projection of high-dimensional data. IEEE Transactions on Visualization and Computer Graphics, 27( 2), 561-571. doi:10.1109/TVCG.2020.3030441

    • NLM

      Doraiswamy H, Tierny J, Silva PJS, Nonato LG, Silva C. TopoMap: a 0-dimensional homology preserving projection of high-dimensional data [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 2): 561-571.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1109/TVCG.2020.3030441

    • Vancouver

      Doraiswamy H, Tierny J, Silva PJS, Nonato LG, Silva C. TopoMap: a 0-dimensional homology preserving projection of high-dimensional data [Internet]. IEEE Transactions on Visualization and Computer Graphics. 2021 ; 27( 2): 561-571.[citado 2024 nov. 05 ] Available from: https://doi.org/10.1109/TVCG.2020.3030441
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