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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://dx.doi.org/10.1016/j.neucom.2022.09.042. Acesso em: 06 dez. 2022.
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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 2022 dez. 06 ] Available from: https://dx.doi.org/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 2022 dez. 06 ] Available from: https://dx.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: 06 dez. 2022.
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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 2022 dez. 06 ] 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 2022 dez. 06 ] Available from: https://doi.org/10.1016/j.neucom.2022.09.042
  • Source: IEEE Transactions on Intelligent Transportation Systems. Unidades: ICMC, EESC

    Subjects: VEÍCULOS AUTÔNOMOS, TRÁFEGO RODOVIÁRIO, ANÁLISE DE TRAJETÓRIAS

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      SILVA, Júnior Anderson Rodrigues da et al. Sparse road network model for autonomous navigation using clothoids. IEEE Transactions on Intelligent Transportation Systems, v. 23, n. 2, p. 885-898, 2022Tradução . . Disponível em: https://doi.org/10.1109/TITS.2020.3016620. Acesso em: 06 dez. 2022.
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      Silva, J. A. R. da, Gomes, I. P., Wolf, D. F., & Grassi Júnior, V. (2022). Sparse road network model for autonomous navigation using clothoids. IEEE Transactions on Intelligent Transportation Systems, 23( 2), 885-898. doi:10.1109/TITS.2020.3016620
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      Silva JAR da, Gomes IP, Wolf DF, Grassi Júnior V. Sparse road network model for autonomous navigation using clothoids [Internet]. IEEE Transactions on Intelligent Transportation Systems. 2022 ; 23( 2): 885-898.[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/TITS.2020.3016620
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      Silva JAR da, Gomes IP, Wolf DF, Grassi Júnior V. Sparse road network model for autonomous navigation using clothoids [Internet]. IEEE Transactions on Intelligent Transportation Systems. 2022 ; 23( 2): 885-898.[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/TITS.2020.3016620
  • Source: International Journal of Control. Unidades: EESC, ICMC

    Subjects: CONTROLE (TEORIA DE SISTEMAS E CONTROLE), CONTROLE ÓTIMO, SISTEMAS LINEARES

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      MASSERA FILHO, Carlos Alberto de Magalhães e TERRA, Marco Henrique e WOLF, Denis Fernando. Optimal guaranteed cost control of discrete-time linear systems subject to structured uncertainties. International Journal of Control, v. 94, n. 4, p. 1132-1142, 2021Tradução . . Disponível em: http://dx.doi.org/10.1080/00207179.2019.1634838. Acesso em: 06 dez. 2022.
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      Massera Filho, C. A. de M., Terra, M. H., & Wolf, D. F. (2021). Optimal guaranteed cost control of discrete-time linear systems subject to structured uncertainties. International Journal of Control, 94( 4), 1132-1142. doi:10.1080/00207179.2019.1634838
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      Massera Filho CA de M, Terra MH, Wolf DF. Optimal guaranteed cost control of discrete-time linear systems subject to structured uncertainties [Internet]. International Journal of Control. 2021 ; 94( 4): 1132-1142.[citado 2022 dez. 06 ] Available from: http://dx.doi.org/10.1080/00207179.2019.1634838
    • Vancouver

      Massera Filho CA de M, Terra MH, Wolf DF. Optimal guaranteed cost control of discrete-time linear systems subject to structured uncertainties [Internet]. International Journal of Control. 2021 ; 94( 4): 1132-1142.[citado 2022 dez. 06 ] Available from: http://dx.doi.org/10.1080/00207179.2019.1634838
  • Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, VEÍCULOS AUTÔNOMOS, CIDADES INTELIGENTES

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      RIDEL, Daniela Alves. Scene compliant spatio-temporal multi-modal multi-agent long-term trajectory forecasting. 2021. Tese (Doutorado) – Universidade de São Paulo, São Carlos, 2021. Disponível em: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-08112021-112852/. Acesso em: 06 dez. 2022.
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      Ridel, D. A. (2021). Scene compliant spatio-temporal multi-modal multi-agent long-term trajectory forecasting (Tese (Doutorado). Universidade de São Paulo, São Carlos. Recuperado de https://www.teses.usp.br/teses/disponiveis/55/55134/tde-08112021-112852/
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      Ridel DA. Scene compliant spatio-temporal multi-modal multi-agent long-term trajectory forecasting [Internet]. 2021 ;[citado 2022 dez. 06 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-08112021-112852/
    • Vancouver

      Ridel DA. Scene compliant spatio-temporal multi-modal multi-agent long-term trajectory forecasting [Internet]. 2021 ;[citado 2022 dez. 06 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-08112021-112852/
  • Source: Engineering Applications of Artificial Intelligence. Unidades: EESC, ICMC

    Subjects: TOMADA DE DECISÃO, ANÁLISE DE DESEMPENHO, APRENDIZADO COMPUTACIONAL

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      NAKAMURA, Angelica Tiemi Mizuno e GRASSI JÚNIOR, Valdir e WOLF, Denis Fernando. An effective combination of loss gradients for multi-task learning applied on instance segmentation and depth estimation. Engineering Applications of Artificial Intelligence, v. 100, p. 1-10, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.engappai.2021.104205. Acesso em: 06 dez. 2022.
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      Nakamura, A. T. M., Grassi Júnior, V., & Wolf, D. F. (2021). An effective combination of loss gradients for multi-task learning applied on instance segmentation and depth estimation. Engineering Applications of Artificial Intelligence, 100, 1-10. doi:10.1016/j.engappai.2021.104205
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      Nakamura ATM, Grassi Júnior V, Wolf DF. An effective combination of loss gradients for multi-task learning applied on instance segmentation and depth estimation [Internet]. Engineering Applications of Artificial Intelligence. 2021 ; 100 1-10.[citado 2022 dez. 06 ] Available from: https://doi.org/10.1016/j.engappai.2021.104205
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      Nakamura ATM, Grassi Júnior V, Wolf DF. An effective combination of loss gradients for multi-task learning applied on instance segmentation and depth estimation [Internet]. Engineering Applications of Artificial Intelligence. 2021 ; 100 1-10.[citado 2022 dez. 06 ] Available from: https://doi.org/10.1016/j.engappai.2021.104205
  • Source: Journal of Intelligent & Robotic Systems. Unidade: ICMC

    Subject: 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: 06 dez. 2022. , 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 2022 dez. 06 ] Available from: https://doi.org/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 2022 dez. 06 ] Available from: https://doi.org/10.1007/s10846-021-01460-9
  • 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: 06 dez. 2022.
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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 2022 dez. 06 ] Available from: https://doi.org/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 2022 dez. 06 ] Available from: https://doi.org/10.1016/j.asoc.2021.107851
  • Source: Proceedings. Conference title: International Conference on Advanced Robotics - ICAR. Unidades: EESC, ICMC

    Subjects: VEÍCULOS AUTÔNOMOS, VISÃO COMPUTACIONAL, PROCESSOS DE MARKOV

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      SILVA, Júnior Anderson Rodrigues da e GRASSI JÚNIOR, Valdir e WOLF, Denis Fernando. Decision making for autonomous vehicles at signalized intersection under uncertain traffic signal phase and timing information. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/ICAR53236.2021.9659406. Acesso em: 06 dez. 2022.
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      Silva, J. A. R. da, Grassi Júnior, V., & Wolf, D. F. (2021). Decision making for autonomous vehicles at signalized intersection under uncertain traffic signal phase and timing information. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICAR53236.2021.9659406
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      Silva JAR da, Grassi Júnior V, Wolf DF. Decision making for autonomous vehicles at signalized intersection under uncertain traffic signal phase and timing information [Internet]. Proceedings. 2021 ;[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/ICAR53236.2021.9659406
    • Vancouver

      Silva JAR da, Grassi Júnior V, Wolf DF. Decision making for autonomous vehicles at signalized intersection under uncertain traffic signal phase and timing information [Internet]. Proceedings. 2021 ;[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/ICAR53236.2021.9659406
  • Source: Proceedings. Conference title: International Conference on Advanced Robotics - ICAR. Unidades: ICMC, EESC

    Subjects: APRENDIZADO COMPUTACIONAL, VISÃO COMPUTACIONAL, VEÍCULOS AUTÔNOMOS

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      HORITA, Luiz Ricardo Takeshi et al. Improving multi-goal and target-driven reinforcement learning with supervised auxiliary task. 2021, Anais.. Los Alamitos: IEEE, 2021. Disponível em: https://doi.org/10.1109/ICAR53236.2021.9659467. Acesso em: 06 dez. 2022.
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      Horita, L. R. T., Nakamura, A. T. M., Wolf, D. F., & Grassi Júnior, V. (2021). Improving multi-goal and target-driven reinforcement learning with supervised auxiliary task. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICAR53236.2021.9659467
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      Horita LRT, Nakamura ATM, Wolf DF, Grassi Júnior V. Improving multi-goal and target-driven reinforcement learning with supervised auxiliary task [Internet]. Proceedings. 2021 ;[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/ICAR53236.2021.9659467
    • Vancouver

      Horita LRT, Nakamura ATM, Wolf DF, Grassi Júnior V. Improving multi-goal and target-driven reinforcement learning with supervised auxiliary task [Internet]. Proceedings. 2021 ;[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/ICAR53236.2021.9659467
  • 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: 06 dez. 2022.
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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 2022 dez. 06 ] 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 2022 dez. 06 ] Available from: https://doi.org/10.1007/s10846-020-01293-y
  • Unidade: ICMC

    Subjects: VEÍCULOS AUTÔNOMOS, PROCESSAMENTO DE IMAGENS, SEGURANÇA NO TRÂNSITO, VISÃO COMPUTACIONAL, ROBÓTICA

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      MATIAS, Lucas Peres Nunes. Environment reconstruction on disparity images using surface features and Generative Adversarial Networks. 2020. Dissertação (Mestrado) – Universidade de São Paulo, São Carlos, 2020. Disponível em: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-27072020-163017/. Acesso em: 06 dez. 2022.
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      Matias, L. P. N. (2020). Environment reconstruction on disparity images using surface features and Generative Adversarial Networks (Dissertação (Mestrado). Universidade de São Paulo, São Carlos. Recuperado de https://www.teses.usp.br/teses/disponiveis/55/55134/tde-27072020-163017/
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      Matias LPN. Environment reconstruction on disparity images using surface features and Generative Adversarial Networks [Internet]. 2020 ;[citado 2022 dez. 06 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-27072020-163017/
    • Vancouver

      Matias LPN. Environment reconstruction on disparity images using surface features and Generative Adversarial Networks [Internet]. 2020 ;[citado 2022 dez. 06 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-27072020-163017/
  • Source: IEEE Robotics and Automation Letters. Unidade: ICMC

    Subjects: ANÁLISE DE TRAJETÓRIAS, GEOMETRIA E MODELAGEM COMPUTACIONAL

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      RIDEL, Daniela Alves et al. Scene compliant trajectory forecast with agent-centric spatio-temporal grids. IEEE Robotics and Automation Letters, v. 5, n. 2, p. 2816-2823, 2020Tradução . . Disponível em: https://doi.org/10.1109/LRA.2020.2974393. Acesso em: 06 dez. 2022.
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      Ridel, D. A., Deo, N., Wolf, D. F., & Trivedi, M. (2020). Scene compliant trajectory forecast with agent-centric spatio-temporal grids. IEEE Robotics and Automation Letters, 5( 2), 2816-2823. doi:10.1109/LRA.2020.2974393
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      Ridel DA, Deo N, Wolf DF, Trivedi M. Scene compliant trajectory forecast with agent-centric spatio-temporal grids [Internet]. IEEE Robotics and Automation Letters. 2020 ; 5( 2): 2816-2823.[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/LRA.2020.2974393
    • Vancouver

      Ridel DA, Deo N, Wolf DF, Trivedi M. Scene compliant trajectory forecast with agent-centric spatio-temporal grids [Internet]. IEEE Robotics and Automation Letters. 2020 ; 5( 2): 2816-2823.[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/LRA.2020.2974393
  • Source: Proceedings. Conference title: International Joint Conference on Neural Networks - IJCNN. Unidades: ICMC, EESC

    Subjects: ALGORITMOS, REDES NEURAIS

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      HORITA, Luiz Ricardo Takeshi e WOLF, Denis Fernando e GRASSI JÚNIOR, Valdir. Effective deep reinforcement learning setups for multiple goals on visual navigation. 2020, Anais.. Piscataway: IEEE, 2020. Disponível em: https://doi.org/10.1109/IJCNN48605.2020.9206917. Acesso em: 06 dez. 2022.
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      Horita, L. R. T., Wolf, D. F., & Grassi Júnior, V. (2020). Effective deep reinforcement learning setups for multiple goals on visual navigation. In Proceedings. Piscataway: IEEE. doi:10.1109/IJCNN48605.2020.9206917
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      Horita LRT, Wolf DF, Grassi Júnior V. Effective deep reinforcement learning setups for multiple goals on visual navigation [Internet]. Proceedings. 2020 ;[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9206917
    • Vancouver

      Horita LRT, Wolf DF, Grassi Júnior V. Effective deep reinforcement learning setups for multiple goals on visual navigation [Internet]. Proceedings. 2020 ;[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9206917
  • Source: Proceedings. Conference title: IEEE Intelligent Vehicles Symposium - IV. Unidade: ICMC

    Subjects: VEÍCULOS AUTÔNOMOS, WIRELESS, CONTROLE DE TRÁFEGO, MOBILIDADE URBANA

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      SANTOS, Tiago Cesar dos et al. Evaluation of lane-merging approaches for connected vehicles. 2019, Anais.. Piscataway: IEEE, 2019. Disponível em: http://dx.doi.org/10.1109/IVS.2019.8813802. Acesso em: 06 dez. 2022.
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      Santos, T. C. dos, Bruno, D. R., Osório, F. S., & Wolf, D. F. (2019). Evaluation of lane-merging approaches for connected vehicles. In Proceedings. Piscataway: IEEE. doi:10.1109/IVS.2019.8813802
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      Santos TC dos, Bruno DR, Osório FS, Wolf DF. Evaluation of lane-merging approaches for connected vehicles [Internet]. Proceedings. 2019 ;[citado 2022 dez. 06 ] Available from: http://dx.doi.org/10.1109/IVS.2019.8813802
    • Vancouver

      Santos TC dos, Bruno DR, Osório FS, Wolf DF. Evaluation of lane-merging approaches for connected vehicles [Internet]. Proceedings. 2019 ;[citado 2022 dez. 06 ] Available from: http://dx.doi.org/10.1109/IVS.2019.8813802
  • Source: Proceedings. Conference title: International Conference on Advanced Robotics - ICAR. Unidade: ICMC

    Subjects: SINALIZAÇÃO DE TRÁFEGO, WIRELESS, VEÍCULOS AUTÔNOMOS, SEGURANÇA NO TRÂNSITO

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      SANTOS, Tiago Cesar dos e WOLF, Denis Fernando. Automated conflict resolution of lane change Utilizing probability collectives. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/ICAR46387.2019.8981609. Acesso em: 06 dez. 2022.
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      Santos, T. C. dos, & Wolf, D. F. (2019). Automated conflict resolution of lane change Utilizing probability collectives. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICAR46387.2019.8981609
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      Santos TC dos, Wolf DF. Automated conflict resolution of lane change Utilizing probability collectives [Internet]. Proceedings. 2019 ;[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/ICAR46387.2019.8981609
    • Vancouver

      Santos TC dos, Wolf DF. Automated conflict resolution of lane change Utilizing probability collectives [Internet]. Proceedings. 2019 ;[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/ICAR46387.2019.8981609
  • Unidade: ICMC

    Subjects: VEÍCULOS AUTÔNOMOS, ARQUITETURA DE SOFTWARE, FALHAS COMPUTACIONAIS, COMPORTAMENTO, TRANSPORTE URBANO, IMPACTOS AMBIENTAIS

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      GOMES, Iago Pacheco. A Software Architecture Proposal for Autonomous Vehicles. 2019. Dissertação (Mestrado) – Universidade de São Paulo, São Carlos, 2019. Disponível em: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-06012020-122648/. Acesso em: 06 dez. 2022.
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      Gomes, I. P. (2019). A Software Architecture Proposal for Autonomous Vehicles (Dissertação (Mestrado). Universidade de São Paulo, São Carlos. Recuperado de https://www.teses.usp.br/teses/disponiveis/55/55134/tde-06012020-122648/
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      Gomes IP. A Software Architecture Proposal for Autonomous Vehicles [Internet]. 2019 ;[citado 2022 dez. 06 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-06012020-122648/
    • Vancouver

      Gomes IP. A Software Architecture Proposal for Autonomous Vehicles [Internet]. 2019 ;[citado 2022 dez. 06 ] Available from: https://www.teses.usp.br/teses/disponiveis/55/55134/tde-06012020-122648/
  • Source: Autonomous Robots. Unidade: ICMC

    Subjects: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, VISÃO COMPUTACIONAL, AERONAVES NÃO TRIPULADAS, OTIMIZAÇÃO MATEMÁTICA

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      VIVALDINI, Kelen C. T. et al. UAV route planning for active disease classification. Autonomous Robots, v. 43, p. 1137-1153, 2019Tradução . . Disponível em: http://dx.doi.org/10.1007/s10514-018-9790-x. Acesso em: 06 dez. 2022.
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      Vivaldini, K. C. T., Martinelli, T. H., Guizilini, V. C., Souza, J. R., Oliveira, M. D. C., Ramos, F., & Wolf, D. F. (2019). UAV route planning for active disease classification. Autonomous Robots, 43, 1137-1153. doi:10.1007/s10514-018-9790-x
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      Vivaldini KCT, Martinelli TH, Guizilini VC, Souza JR, Oliveira MDC, Ramos F, Wolf DF. UAV route planning for active disease classification [Internet]. Autonomous Robots. 2019 ; 43 1137-1153.[citado 2022 dez. 06 ] Available from: http://dx.doi.org/10.1007/s10514-018-9790-x
    • Vancouver

      Vivaldini KCT, Martinelli TH, Guizilini VC, Souza JR, Oliveira MDC, Ramos F, Wolf DF. UAV route planning for active disease classification [Internet]. Autonomous Robots. 2019 ; 43 1137-1153.[citado 2022 dez. 06 ] Available from: http://dx.doi.org/10.1007/s10514-018-9790-x
  • Source: Proceedings. Conference title: International Conference on Advanced Robotics - ICAR. Unidade: ICMC

    Subjects: FALHA, VEÍCULOS AUTÔNOMOS, SEGURANÇA NO TRÂNSITO

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    • ABNT

      GOMES, Iago Pachêco e WOLF, Denis Fernando. A health monitoring system with hybrid bayesian network for autonomous vehicle. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/ICAR46387.2019.8981565. Acesso em: 06 dez. 2022.
    • APA

      Gomes, I. P., & Wolf, D. F. (2019). A health monitoring system with hybrid bayesian network for autonomous vehicle. In Proceedings. Los Alamitos: IEEE. doi:10.1109/ICAR46387.2019.8981565
    • NLM

      Gomes IP, Wolf DF. A health monitoring system with hybrid bayesian network for autonomous vehicle [Internet]. Proceedings. 2019 ;[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/ICAR46387.2019.8981565
    • Vancouver

      Gomes IP, Wolf DF. A health monitoring system with hybrid bayesian network for autonomous vehicle [Internet]. Proceedings. 2019 ;[citado 2022 dez. 06 ] Available from: https://doi.org/10.1109/ICAR46387.2019.8981565
  • Source: Proceedings. Conference title: IEEE Intelligent Vehicles Symposium - IV. Unidade: ICMC

    Subjects: IMAGEM 3D, VISÃO COMPUTACIONAL, REDES NEURAIS, VEÍCULOS AUTÔNOMOS

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    • ABNT

      MATIAS, Lucas Peres Nunes et al. VeIGAN: vectorial inpainting generative adversarial network for depth maps Object removal. 2019, Anais.. Piscataway: IEEE, 2019. Disponível em: http://dx.doi.org/10.1109/IVS.2019.8814157. Acesso em: 06 dez. 2022.
    • APA

      Matias, L. P. N., Sons, M., Souza, J. R. de, Wolf, D. F., & Stiller, C. (2019). VeIGAN: vectorial inpainting generative adversarial network for depth maps Object removal. In Proceedings. Piscataway: IEEE. doi:10.1109/IVS.2019.8814157
    • NLM

      Matias LPN, Sons M, Souza JR de, Wolf DF, Stiller C. VeIGAN: vectorial inpainting generative adversarial network for depth maps Object removal [Internet]. Proceedings. 2019 ;[citado 2022 dez. 06 ] Available from: http://dx.doi.org/10.1109/IVS.2019.8814157
    • Vancouver

      Matias LPN, Sons M, Souza JR de, Wolf DF, Stiller C. VeIGAN: vectorial inpainting generative adversarial network for depth maps Object removal [Internet]. Proceedings. 2019 ;[citado 2022 dez. 06 ] Available from: http://dx.doi.org/10.1109/IVS.2019.8814157

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