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Filtros : "Burwitz, Vassily V." Limpar

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  • Relatorio tecnico

    Processing of massive rutherford back-scattering spectrometry data by artificial neural networks (2022)

    Guimarães, Renato dos Santos ; Bach, Simon; Burwitz, Vassily V.; Hiret, Paul; Mayer, Matej; Silva, Tiago Fiorini da ; Rodrigues, Cleber Lima ; Tabacniks, Manfredo Harri

    Unidade: IF

    Subjects: ESPECTROSCOPIA, REDES NEURAIS

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

    • ABNT

      GUIMARÃES, Renato dos Santos et al. Processing of massive rutherford back-scattering spectrometry data by artificial neural networks. . São Paulo: Instituto de Física, Universidade de São Paulo. Disponível em: https://arxiv.org/ftp/arxiv/papers/2205/2205.05680.pdf. Acesso em: 24 maio 2024. , 2022

    • APA

      Guimarães, R. dos S., Bach, S., Burwitz, V. V., Hiret, P., Mayer, M., Silva, T. F. da, et al. (2022). Processing of massive rutherford back-scattering spectrometry data by artificial neural networks. São Paulo: Instituto de Física, Universidade de São Paulo. Recuperado de https://arxiv.org/ftp/arxiv/papers/2205/2205.05680.pdf

    • NLM

      Guimarães R dos S, Bach S, Burwitz VV, Hiret P, Mayer M, Silva TF da, Rodrigues CL, Tabacniks MH. Processing of massive rutherford back-scattering spectrometry data by artificial neural networks [Internet]. 2022 ;[citado 2024 maio 24 ] Available from: https://arxiv.org/ftp/arxiv/papers/2205/2205.05680.pdf

    • Vancouver

      Guimarães R dos S, Bach S, Burwitz VV, Hiret P, Mayer M, Silva TF da, Rodrigues CL, Tabacniks MH. Processing of massive rutherford back-scattering spectrometry data by artificial neural networks [Internet]. 2022 ;[citado 2024 maio 24 ] Available from: https://arxiv.org/ftp/arxiv/papers/2205/2205.05680.pdf

  • Artigo de periodico

    Processing of massive Rutherford Back-scattering Spectrometry data by artificial neural networks (2021)

    Guimarães, Renato da S.; Silva, Tiago Fiorini da ; Rodrigues, Cleber ; Tabacniks, Manfredo ; Bach, Simon; Burwitz, Vassily V.; Paul Hiret ; Matej Mayer

    Source: Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms. Unidade: IF

    Subjects: REDES NEURAIS, INTELIGÊNCIA ARTIFICIAL, ESPECTROMETRIA, ESPALHAMENTO, PROCESSAMENTO DE DADOS

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

    • ABNT

      GUIMARÃES, Renato da S. et al. Processing of massive Rutherford Back-scattering Spectrometry data by artificial neural networks. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, v. 493, p. 28-34, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.nimb.2021.02.010. Acesso em: 24 maio 2024.

    • APA

      Guimarães, R. da S., Silva, T. F. da, Rodrigues, C., Tabacniks, M., Bach, S., Burwitz, V. V., et al. (2021). Processing of massive Rutherford Back-scattering Spectrometry data by artificial neural networks. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 493, 28-34. doi:10.1016/j.nimb.2021.02.010

    • NLM

      Guimarães R da S, Silva TF da, Rodrigues C, Tabacniks M, Bach S, Burwitz VV, Paul Hiret, Matej Mayer. Processing of massive Rutherford Back-scattering Spectrometry data by artificial neural networks [Internet]. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms. 2021 ; 493 28-34.[citado 2024 maio 24 ] Available from: https://doi.org/10.1016/j.nimb.2021.02.010

    • Vancouver

      Guimarães R da S, Silva TF da, Rodrigues C, Tabacniks M, Bach S, Burwitz VV, Paul Hiret, Matej Mayer. Processing of massive Rutherford Back-scattering Spectrometry data by artificial neural networks [Internet]. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms. 2021 ; 493 28-34.[citado 2024 maio 24 ] Available from: https://doi.org/10.1016/j.nimb.2021.02.010
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