Filtros : "ELETROQUÍMICA" "IQSC" "Singapura" Limpar

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  • Unidades: IQSC, IFSC

    Assunto: ELETROQUÍMICA

    Versão PublicadaAcesso à fonteHow to cite
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    • ABNT

      BRAZACA, Lais Canniatti e RAYMUNDO-PEREIRA, Paulo Augusto. Discover Electrochemistry. . Singapura: Springer Singapore. Disponível em: https://link.springer.com/journal/44373/editors. Acesso em: 19 nov. 2024. , 2024
    • APA

      Brazaca, L. C., & Raymundo-Pereira, P. A. (2024). Discover Electrochemistry. Singapura: Springer Singapore. Recuperado de https://link.springer.com/journal/44373/editors
    • NLM

      Brazaca LC, Raymundo-Pereira PA. Discover Electrochemistry [Internet]. 2024 ;[citado 2024 nov. 19 ] Available from: https://link.springer.com/journal/44373/editors
    • Vancouver

      Brazaca LC, Raymundo-Pereira PA. Discover Electrochemistry [Internet]. 2024 ;[citado 2024 nov. 19 ] Available from: https://link.springer.com/journal/44373/editors
  • Source: Machine learning for advanced functional materials. Unidades: IFSC, IQSC

    Subjects: ELETROQUÍMICA, APRENDIZADO COMPUTACIONAL, SENSOR, INTELIGÊNCIA ARTIFICIAL

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    • ABNT

      IBÁÑEZ-REDÍN, Glenda Gisela et al. A machine learning approach in wearable technologies. Machine learning for advanced functional materials. Tradução . Singapore: Springer, 2023. . Disponível em: https://doi.org/10.1007/978-981-99-0393-1_3. Acesso em: 19 nov. 2024.
    • APA

      Ibáñez-Redín, G. G., Duarte, O. S., Cagnani, G. R., & Oliveira Junior, O. N. de. (2023). A machine learning approach in wearable technologies. In Machine learning for advanced functional materials. Singapore: Springer. doi:10.1007/978-981-99-0393-1_3
    • NLM

      Ibáñez-Redín GG, Duarte OS, Cagnani GR, Oliveira Junior ON de. A machine learning approach in wearable technologies [Internet]. In: Machine learning for advanced functional materials. Singapore: Springer; 2023. [citado 2024 nov. 19 ] Available from: https://doi.org/10.1007/978-981-99-0393-1_3
    • Vancouver

      Ibáñez-Redín GG, Duarte OS, Cagnani GR, Oliveira Junior ON de. A machine learning approach in wearable technologies [Internet]. In: Machine learning for advanced functional materials. Singapore: Springer; 2023. [citado 2024 nov. 19 ] Available from: https://doi.org/10.1007/978-981-99-0393-1_3
  • Source: Machine learning for advanced functional materials. Unidades: IFSC, IQSC

    Subjects: ELETROQUÍMICA, SENSORES QUÍMICOS, SENSORES ÓPTICOS, INTELIGÊNCIA ARTIFICIAL

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    • ABNT

      MATERON, Elsa Maria et al. Recent advances in machine learning for electrochemical, optical, and gas sensors. Machine learning for advanced functional materials. Tradução . Singapore: Springer, 2023. . Disponível em: https://doi.org/10.1007/978-981-99-0393-1_6. Acesso em: 19 nov. 2024.
    • APA

      Materon, E. M., Silva, F. S. R. da, Ribas, L. C., Joshi, N. K. J., Bruno, O. M., Carrilho, E., & Oliveira Junior, O. N. de. (2023). Recent advances in machine learning for electrochemical, optical, and gas sensors. In Machine learning for advanced functional materials. Singapore: Springer. doi:10.1007/978-981-99-0393-1_6
    • NLM

      Materon EM, Silva FSR da, Ribas LC, Joshi NKJ, Bruno OM, Carrilho E, Oliveira Junior ON de. Recent advances in machine learning for electrochemical, optical, and gas sensors [Internet]. In: Machine learning for advanced functional materials. Singapore: Springer; 2023. [citado 2024 nov. 19 ] Available from: https://doi.org/10.1007/978-981-99-0393-1_6
    • Vancouver

      Materon EM, Silva FSR da, Ribas LC, Joshi NKJ, Bruno OM, Carrilho E, Oliveira Junior ON de. Recent advances in machine learning for electrochemical, optical, and gas sensors [Internet]. In: Machine learning for advanced functional materials. Singapore: Springer; 2023. [citado 2024 nov. 19 ] Available from: https://doi.org/10.1007/978-981-99-0393-1_6

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