Filtros : "Wolf, Denis Fernando" "Holanda" "ICMC" Removidos: "Meneghetti, Renata Cristina Geromel" "Índia" "EDITOR DE PERIODICO" "IEA" Limpar

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  • Source: Neurocomputing. Unidades: EESC, ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, ENGENHARIA ELÉTRICA

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      NAKAMURA, Angelica Tiemi Mizuno e GRASSI JÚNIOR, Valdir e WOLF, Denis Fernando. Leveraging convergence behavior to balance conflicting tasks in multitask learning. Neurocomputing, v. 511, p. 43-53, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2022.09.042. Acesso em: 10 ago. 2024.
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      Nakamura, A. T. M., Grassi Júnior, V., & Wolf, D. F. (2022). Leveraging convergence behavior to balance conflicting tasks in multitask learning. Neurocomputing, 511, 43-53. doi:10.1016/j.neucom.2022.09.042
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      Nakamura ATM, Grassi Júnior V, Wolf DF. Leveraging convergence behavior to balance conflicting tasks in multitask learning [Internet]. Neurocomputing. 2022 ; 511 43-53.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1016/j.neucom.2022.09.042
    • Vancouver

      Nakamura ATM, Grassi Júnior V, Wolf DF. Leveraging convergence behavior to balance conflicting tasks in multitask learning [Internet]. Neurocomputing. 2022 ; 511 43-53.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1016/j.neucom.2022.09.042
  • Source: Neurocomputing. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, ANÁLISE DE DESEMPENHO

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      NAKAMURA, Angelica Tiemi Mizuno e GRASSI JÚNIOR, Valdir e WOLF, Denis Fernando. Leveraging convergence behavior to balance conflicting tasks in multitask learning. Neurocomputing, v. 511, p. 43-53, 2022Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2022.09.042. Acesso em: 10 ago. 2024.
    • APA

      Nakamura, A. T. M., Grassi Júnior, V., & Wolf, D. F. (2022). Leveraging convergence behavior to balance conflicting tasks in multitask learning. Neurocomputing, 511, 43-53. doi:10.1016/j.neucom.2022.09.042
    • NLM

      Nakamura ATM, Grassi Júnior V, Wolf DF. Leveraging convergence behavior to balance conflicting tasks in multitask learning [Internet]. Neurocomputing. 2022 ; 511 43-53.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1016/j.neucom.2022.09.042
    • Vancouver

      Nakamura ATM, Grassi Júnior V, Wolf DF. Leveraging convergence behavior to balance conflicting tasks in multitask learning [Internet]. Neurocomputing. 2022 ; 511 43-53.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1016/j.neucom.2022.09.042
  • Source: Applied Soft Computing. Unidade: ICMC

    Subjects: RECONHECIMENTO DE IMAGEM, REDES NEURAIS

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      WATANABE, Thomio e WOLF, Denis Fernando. Image classification in frequency domain with 2SReLU: a second harmonics superposition activation function. Applied Soft Computing, v. No 2021, p. 1-10, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.asoc.2021.107851. Acesso em: 10 ago. 2024.
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      Watanabe, T., & Wolf, D. F. (2021). Image classification in frequency domain with 2SReLU: a second harmonics superposition activation function. Applied Soft Computing, No 2021, 1-10. doi:10.1016/j.asoc.2021.107851
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      Watanabe T, Wolf DF. Image classification in frequency domain with 2SReLU: a second harmonics superposition activation function [Internet]. Applied Soft Computing. 2021 ; No 2021 1-10.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1016/j.asoc.2021.107851
    • Vancouver

      Watanabe T, Wolf DF. Image classification in frequency domain with 2SReLU: a second harmonics superposition activation function [Internet]. Applied Soft Computing. 2021 ; No 2021 1-10.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1016/j.asoc.2021.107851
  • Source: Journal of Intelligent & Robotic Systems. Unidade: ICMC

    Assunto: ROBÓTICA

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      ICAR 2019 Special Issue [Editorial]. Journal of Intelligent & Robotic Systems. Dordrecht: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. Disponível em: https://doi.org/10.1007/s10846-021-01460-9. Acesso em: 10 ago. 2024. , 2021
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      ICAR 2019 Special Issue [Editorial]. (2021). ICAR 2019 Special Issue [Editorial]. Journal of Intelligent & Robotic Systems. Dordrecht: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo. doi:10.1007/s10846-021-01460-9
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      ICAR 2019 Special Issue [Editorial] [Internet]. Journal of Intelligent & Robotic Systems. 2021 ; 102 1-2.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1007/s10846-021-01460-9
    • Vancouver

      ICAR 2019 Special Issue [Editorial] [Internet]. Journal of Intelligent & Robotic Systems. 2021 ; 102 1-2.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1007/s10846-021-01460-9
  • Source: Journal of Intelligent & Robotic Systems. Unidade: ICMC

    Subjects: VEÍCULOS AUTÔNOMOS, FALHAS COMPUTACIONAIS, APRENDIZADO COMPUTACIONAL, SISTEMAS DINÂMICOS

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      GOMES, Iago Pachêco e WOLF, Denis Fernando. Health monitoring system for autonomous vehicles using dynamic bayesian networks for diagnosis and prognosis. Journal of Intelligent & Robotic Systems, v. 101, n. Ja 2021, p. 1-21, 2021Tradução . . Disponível em: https://doi.org/10.1007/s10846-020-01293-y. Acesso em: 10 ago. 2024.
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      Gomes, I. P., & Wolf, D. F. (2021). Health monitoring system for autonomous vehicles using dynamic bayesian networks for diagnosis and prognosis. Journal of Intelligent & Robotic Systems, 101( Ja 2021), 1-21. doi:10.1007/s10846-020-01293-y
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      Gomes IP, Wolf DF. Health monitoring system for autonomous vehicles using dynamic bayesian networks for diagnosis and prognosis [Internet]. Journal of Intelligent & Robotic Systems. 2021 ; 101( Ja 2021): 1-21.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1007/s10846-020-01293-y
    • Vancouver

      Gomes IP, Wolf DF. Health monitoring system for autonomous vehicles using dynamic bayesian networks for diagnosis and prognosis [Internet]. Journal of Intelligent & Robotic Systems. 2021 ; 101( Ja 2021): 1-21.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1007/s10846-020-01293-y
  • Source: Engineering Applications of Artificial Intelligence. Unidade: ICMC

    Subjects: SISTEMAS EMBUTIDOS, COMPUTAÇÃO EVOLUTIVA, ROBÓTICA

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      SALES, Daniel O et al. Adaptive finite state machine based visual autonomous navigation system. Engineering Applications of Artificial Intelligence, v. 29, p. 152-162, 2014Tradução . . Disponível em: https://doi.org/10.1016/j.engappai.2013.12.006. Acesso em: 10 ago. 2024.
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      Sales, D. O., Correa, D. O., Fernandes, L. C., Wolf, D. F., & Osório, F. S. (2014). Adaptive finite state machine based visual autonomous navigation system. Engineering Applications of Artificial Intelligence, 29, 152-162. doi:10.1016/j.engappai.2013.12.006
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      Sales DO, Correa DO, Fernandes LC, Wolf DF, Osório FS. Adaptive finite state machine based visual autonomous navigation system [Internet]. Engineering Applications of Artificial Intelligence. 2014 ; 29 152-162.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1016/j.engappai.2013.12.006
    • Vancouver

      Sales DO, Correa DO, Fernandes LC, Wolf DF, Osório FS. Adaptive finite state machine based visual autonomous navigation system [Internet]. Engineering Applications of Artificial Intelligence. 2014 ; 29 152-162.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1016/j.engappai.2013.12.006
  • Source: Journal of Systems Architecture. Unidades: ICMC, EESC

    Subjects: SISTEMAS DE INFORMAÇÃO, ENGENHARIA DE SOFTWARE

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      FERNANDES, Leandro C et al. CaRINA intelligent robotic car: architectural design and applications. Journal of Systems Architecture, v. 60, n. 4, p. 372-392, 2014Tradução . . Disponível em: https://doi.org/10.1016/j.sysarc.2013.12.003. Acesso em: 10 ago. 2024.
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      Fernandes, L. C., Souza, J. R., Pessin, G., Shinzato, P. Y., Sales, D., Mendes, C., et al. (2014). CaRINA intelligent robotic car: architectural design and applications. Journal of Systems Architecture, 60( 4), 372-392. doi:10.1016/j.sysarc.2013.12.003
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      Fernandes LC, Souza JR, Pessin G, Shinzato PY, Sales D, Mendes C, Prado M, Klaser R, Magalhães AC, Hata A, Pigatto D, Branco KRLJC, Grassi Júnior V, Osório FS, Wolf DF. CaRINA intelligent robotic car: architectural design and applications [Internet]. Journal of Systems Architecture. 2014 ; 60( 4): 372-392.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1016/j.sysarc.2013.12.003
    • Vancouver

      Fernandes LC, Souza JR, Pessin G, Shinzato PY, Sales D, Mendes C, Prado M, Klaser R, Magalhães AC, Hata A, Pigatto D, Branco KRLJC, Grassi Júnior V, Osório FS, Wolf DF. CaRINA intelligent robotic car: architectural design and applications [Internet]. Journal of Systems Architecture. 2014 ; 60( 4): 372-392.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1016/j.sysarc.2013.12.003
  • Source: Journal of Intelligent and Fuzzy Systems. Unidade: ICMC

    Subjects: VEÍCULOS AUTÔNOMOS, REDES NEURAIS, VISÃO COMPUTACIONAL

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      PESSIN, Gustavo et al. Investigation on the evolution of a robotic controller for autonomous vehicle navigation. Journal of Intelligent and Fuzzy Systems, v. 27, n. 6, p. 3047-3058, 2014Tradução . . Disponível em: https://doi.org/10.3233/IFS-141262. Acesso em: 10 ago. 2024.
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      Pessin, G., Souza, J. R. de, Osório, F. S., Faiçal, B. S., Filho, G. P. R., Ueyama, J., et al. (2014). Investigation on the evolution of a robotic controller for autonomous vehicle navigation. Journal of Intelligent and Fuzzy Systems, 27( 6), 3047-3058. doi:10.3233/IFS-141262
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      Pessin G, Souza JR de, Osório FS, Faiçal BS, Filho GPR, Ueyama J, Vargas PA, Wolf DF. Investigation on the evolution of a robotic controller for autonomous vehicle navigation [Internet]. Journal of Intelligent and Fuzzy Systems. 2014 ; 27( 6): 3047-3058.[citado 2024 ago. 10 ] Available from: https://doi.org/10.3233/IFS-141262
    • Vancouver

      Pessin G, Souza JR de, Osório FS, Faiçal BS, Filho GPR, Ueyama J, Vargas PA, Wolf DF. Investigation on the evolution of a robotic controller for autonomous vehicle navigation [Internet]. Journal of Intelligent and Fuzzy Systems. 2014 ; 27( 6): 3047-3058.[citado 2024 ago. 10 ] Available from: https://doi.org/10.3233/IFS-141262
  • Source: Neurocomputing. Unidade: ICMC

    Subjects: SISTEMAS EMBUTIDOS, ROBÓTICA

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      SOUZA, Jefferson Rodrigo de et al. Vision-based waypoint following using templates and artificial neural networks. 2013, Anais.. Amsterdam: Elsevier, 2013. p. 77-80. Disponível em: https://doi.org/10.1016/j.neucom.2012.07.040. Acesso em: 10 ago. 2024.
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      Souza, J. R. de, Pessin, G., Shinzato, P. Y., Osório, F. S., & Wolf, D. F. (2013). Vision-based waypoint following using templates and artificial neural networks. In Neurocomputing (Vol. 107, p. 77-80). Amsterdam: Elsevier. doi:10.1016/j.neucom.2012.07.040
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      Souza JR de, Pessin G, Shinzato PY, Osório FS, Wolf DF. Vision-based waypoint following using templates and artificial neural networks [Internet]. Neurocomputing. 2013 ; 107 77-80.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1016/j.neucom.2012.07.040
    • Vancouver

      Souza JR de, Pessin G, Shinzato PY, Osório FS, Wolf DF. Vision-based waypoint following using templates and artificial neural networks [Internet]. Neurocomputing. 2013 ; 107 77-80.[citado 2024 ago. 10 ] Available from: https://doi.org/10.1016/j.neucom.2012.07.040
  • Unidade: ICMC

    Subjects: SISTEMAS EMBUTIDOS, COMPUTAÇÃO EVOLUTIVA, ROBÓTICA

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      SHINZATO, Patrick Yuri e WOLF, Denis Fernando. A road following approach using artificial neural networks combinations. 2011Tradução . . Disponível em: https://doi.org/10.1007/s10711-010-9565-9. Acesso em: 10 ago. 2024.
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      Shinzato, P. Y., & Wolf, D. F. (2011). A road following approach using artificial neural networks combinations. doi:10.1007/s10711-010-9565-9
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      Shinzato PY, Wolf DF. A road following approach using artificial neural networks combinations [Internet]. 2011 ;[citado 2024 ago. 10 ] Available from: https://doi.org/10.1007/s10711-010-9565-9
    • Vancouver

      Shinzato PY, Wolf DF. A road following approach using artificial neural networks combinations [Internet]. 2011 ;[citado 2024 ago. 10 ] Available from: https://doi.org/10.1007/s10711-010-9565-9

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