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  • Source: Neural Computing and Applications. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, PREVISÃO (ANÁLISE DE SÉRIES TEMPORAIS), MERCADO FINANCEIRO

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    • ABNT

      REIS FILHO, Ivan José dos et al. How do financial time series enhance the detection of news significance in market movements?: A study using graph neural networks with heterogeneous representations. Neural Computing and Applications, v. 37, n. Ja 2025, p. 1307-1319, 2025Tradução . . Disponível em: https://doi.org/10.1007/s00521-024-10418-5. Acesso em: 14 nov. 2025.
    • APA

      Reis Filho, I. J. dos, Gôlo, M. P. S., Marcacini, R. M., & Rezende, S. O. (2025). How do financial time series enhance the detection of news significance in market movements?: A study using graph neural networks with heterogeneous representations. Neural Computing and Applications, 37( Ja 2025), 1307-1319. doi:10.1007/s00521-024-10418-5
    • NLM

      Reis Filho IJ dos, Gôlo MPS, Marcacini RM, Rezende SO. How do financial time series enhance the detection of news significance in market movements?: A study using graph neural networks with heterogeneous representations [Internet]. Neural Computing and Applications. 2025 ; 37( Ja 2025): 1307-1319.[citado 2025 nov. 14 ] Available from: https://doi.org/10.1007/s00521-024-10418-5
    • Vancouver

      Reis Filho IJ dos, Gôlo MPS, Marcacini RM, Rezende SO. How do financial time series enhance the detection of news significance in market movements?: A study using graph neural networks with heterogeneous representations [Internet]. Neural Computing and Applications. 2025 ; 37( Ja 2025): 1307-1319.[citado 2025 nov. 14 ] Available from: https://doi.org/10.1007/s00521-024-10418-5
  • Source: Neural Computing and Applications. Conference titles: LatinX in AI at NeurIPS. Unidade: IME

    Assunto: MATEMÁTICA APLICADA

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    • ABNT

      POLO, Felipe Maia e VICENTE, Renato. Effective sample size, dimensionality, and generalization in covariate shift adaptation. Neural Computing and Applications. Godalming: Instituto de Matemática e Estatística, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/s00521-021-06615-1. Acesso em: 14 nov. 2025. , 2023
    • APA

      Polo, F. M., & Vicente, R. (2023). Effective sample size, dimensionality, and generalization in covariate shift adaptation. Neural Computing and Applications. Godalming: Instituto de Matemática e Estatística, Universidade de São Paulo. doi:10.1007/s00521-021-06615-1
    • NLM

      Polo FM, Vicente R. Effective sample size, dimensionality, and generalization in covariate shift adaptation [Internet]. Neural Computing and Applications. 2023 ; 35( 25): 18187-18199.[citado 2025 nov. 14 ] Available from: https://doi.org/10.1007/s00521-021-06615-1
    • Vancouver

      Polo FM, Vicente R. Effective sample size, dimensionality, and generalization in covariate shift adaptation [Internet]. Neural Computing and Applications. 2023 ; 35( 25): 18187-18199.[citado 2025 nov. 14 ] Available from: https://doi.org/10.1007/s00521-021-06615-1
  • Source: Neural Computing and Applications. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, ELETROENCEFALOGRAFIA, EPILEPSIA, DIAGNÓSTICO POR COMPUTADOR, TECNOLOGIAS DA SAÚDE

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    • ABNT

      VARGAS, Dionathan Luan de et al. Feature extraction and selection from electroencephalogram signals for epileptic seizure diagnosis. Neural Computing and Applications, v. 35, n. 16, p. 12195-12219, 2023Tradução . . Disponível em: https://doi.org/10.1007/s00521-023-08350-1. Acesso em: 14 nov. 2025.
    • APA

      Vargas, D. L. de, Oliva, J. T., Teixeira, M., Casanova, D., & Rosa, J. L. G. (2023). Feature extraction and selection from electroencephalogram signals for epileptic seizure diagnosis. Neural Computing and Applications, 35( 16), 12195-12219. doi:10.1007/s00521-023-08350-1
    • NLM

      Vargas DL de, Oliva JT, Teixeira M, Casanova D, Rosa JLG. Feature extraction and selection from electroencephalogram signals for epileptic seizure diagnosis [Internet]. Neural Computing and Applications. 2023 ; 35( 16): 12195-12219.[citado 2025 nov. 14 ] Available from: https://doi.org/10.1007/s00521-023-08350-1
    • Vancouver

      Vargas DL de, Oliva JT, Teixeira M, Casanova D, Rosa JLG. Feature extraction and selection from electroencephalogram signals for epileptic seizure diagnosis [Internet]. Neural Computing and Applications. 2023 ; 35( 16): 12195-12219.[citado 2025 nov. 14 ] Available from: https://doi.org/10.1007/s00521-023-08350-1
  • Source: Neural Computing and Applications. Unidade: ICMC

    Subjects: REDES NEURAIS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE PADRÕES, ACÚSTICA, MONITORAMENTO AMBIENTAL, PÁSSAROS, ANURA

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    • ABNT

      DIAS, Fabio Felix e PONTI, Moacir Antonelli e MINGHIM, Rosane. A classification and quantification approach to generate features in soundscape ecology using neural networks. Neural Computing and Applications, v. 34, n. 3, p. 1923-1937, 2022Tradução . . Disponível em: https://doi.org/10.1007/s00521-021-06501-w. Acesso em: 14 nov. 2025.
    • APA

      Dias, F. F., Ponti, M. A., & Minghim, R. (2022). A classification and quantification approach to generate features in soundscape ecology using neural networks. Neural Computing and Applications, 34( 3), 1923-1937. doi:10.1007/s00521-021-06501-w
    • NLM

      Dias FF, Ponti MA, Minghim R. A classification and quantification approach to generate features in soundscape ecology using neural networks [Internet]. Neural Computing and Applications. 2022 ; 34( 3): 1923-1937.[citado 2025 nov. 14 ] Available from: https://doi.org/10.1007/s00521-021-06501-w
    • Vancouver

      Dias FF, Ponti MA, Minghim R. A classification and quantification approach to generate features in soundscape ecology using neural networks [Internet]. Neural Computing and Applications. 2022 ; 34( 3): 1923-1937.[citado 2025 nov. 14 ] Available from: https://doi.org/10.1007/s00521-021-06501-w
  • Source: Neural Computing and Applications. Unidade: ICMC

    Subjects: RECONHECIMENTO DE IMAGEM, APRENDIZADO COMPUTACIONAL

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    • ABNT

      RESENDE, Damares Crystina Oliveira de e PONTI, Moacir Antonelli. Robust image features for classification and zero-shot tasks by merging visual and semantic attributes. Neural Computing and Applications, v. 34, n. 6, p. 4459-4471, 2022Tradução . . Disponível em: https://doi.org/10.1007/s00521-021-06601-7. Acesso em: 14 nov. 2025.
    • APA

      Resende, D. C. O. de, & Ponti, M. A. (2022). Robust image features for classification and zero-shot tasks by merging visual and semantic attributes. Neural Computing and Applications, 34( 6), 4459-4471. doi:10.1007/s00521-021-06601-7
    • NLM

      Resende DCO de, Ponti MA. Robust image features for classification and zero-shot tasks by merging visual and semantic attributes [Internet]. Neural Computing and Applications. 2022 ; 34( 6): 4459-4471.[citado 2025 nov. 14 ] Available from: https://doi.org/10.1007/s00521-021-06601-7
    • Vancouver

      Resende DCO de, Ponti MA. Robust image features for classification and zero-shot tasks by merging visual and semantic attributes [Internet]. Neural Computing and Applications. 2022 ; 34( 6): 4459-4471.[citado 2025 nov. 14 ] Available from: https://doi.org/10.1007/s00521-021-06601-7

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