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Artigo de periodico
Leveraging convergence behavior to balance conflicting tasks in multitask learning (2022)
Nakamura, Angelica Tiemi Mizuno ; Grassi Júnior, Valdir ; Wolf, Denis Fernando
Source: Neurocomputing. Unidades: EESC, ICMC
Subjects: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, ENGENHARIA ELÉTRICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 27 nov. 2025.
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 2025 nov. 27 ] 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 2025 nov. 27 ] Available from: https://doi.org/10.1016/j.neucom.2022.09.042
Artigo de periodico
Sparse road network model for autonomous navigation using clothoids (2022)
Silva, Júnior Anderson Rodrigues da ; Gomes, Iago Pachêco ; Wolf, Denis Fernando ; Grassi Júnior, Valdir
Source: IEEE Transactions on Intelligent Transportation Systems. Unidades: ICMC, EESC
Subjects: VEÍCULOS AUTÔNOMOS, TRÁFEGO RODOVIÁRIO, ANÁLISE DE TRAJETÓRIAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 27 nov. 2025.
APA
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
NLM
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 2025 nov. 27 ] Available from: https://doi.org/10.1109/TITS.2020.3016620
Vancouver
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 2025 nov. 27 ] Available from: https://doi.org/10.1109/TITS.2020.3016620
Artigo de periodico
An effective combination of loss gradients for multi-task learning applied on instance segmentation and depth estimation (2021)
Nakamura, Angelica Tiemi Mizuno ; Grassi Júnior, Valdir ; Wolf, Denis Fernando
Source: Engineering Applications of Artificial Intelligence. Unidades: EESC, ICMC
Subjects: TOMADA DE DECISÃO, ANÁLISE DE DESEMPENHO, APRENDIZADO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 27 nov. 2025.
APA
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
NLM
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 2025 nov. 27 ] Available from: https://doi.org/10.1016/j.engappai.2021.104205
Vancouver
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 2025 nov. 27 ] Available from: https://doi.org/10.1016/j.engappai.2021.104205
Artigo de periodico
Health monitoring system for autonomous vehicles using dynamic bayesian networks for diagnosis and prognosis (2021)
Gomes, Iago Pachêco ; Wolf, Denis Fernando
Source: Journal of Intelligent & Robotic Systems. Unidade: ICMC
Subjects: VEÍCULOS AUTÔNOMOS, FALHAS COMPUTACIONAIS, APRENDIZADO COMPUTACIONAL, SISTEMAS DINÂMICOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 27 nov. 2025.
APA
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
NLM
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 2025 nov. 27 ] 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 2025 nov. 27 ] Available from: https://doi.org/10.1007/s10846-020-01293-y
Artigo de periodico
Scene compliant trajectory forecast with agent-centric spatio-temporal grids (2020)
Ridel, Daniela Alves ; Deo, Nachiket; Wolf, Denis Fernando ; Trivedi, Mohan
Source: IEEE Robotics and Automation Letters. Unidade: ICMC
Subjects: ANÁLISE DE TRAJETÓRIAS, GEOMETRIA E MODELAGEM COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 27 nov. 2025.
APA
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
NLM
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 2025 nov. 27 ] 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 2025 nov. 27 ] Available from: https://doi.org/10.1109/LRA.2020.2974393
Trabalho de evento
Effective deep reinforcement learning setups for multiple goals on visual navigation (2020)
Horita, Luiz Ricardo Takeshi ; Wolf, Denis Fernando ; Grassi Júnior, Valdir
Source: Proceedings. Conference titles: International Joint Conference on Neural Networks - IJCNN. Unidades: ICMC, EESC
Subjects: ALGORITMOS, REDES NEURAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
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: 27 nov. 2025.
APA
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
NLM
Horita LRT, Wolf DF, Grassi Júnior V. Effective deep reinforcement learning setups for multiple goals on visual navigation [Internet]. Proceedings. 2020 ;[citado 2025 nov. 27 ] 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 2025 nov. 27 ] Available from: https://doi.org/10.1109/IJCNN48605.2020.9206917
Trabalho de evento
Instance segmentation as image segmentation annotation (2019)
Watanabe, Thomio ; Wolf, Denis Fernando
Source: Proceedings. Conference titles: IEEE Intelligent Vehicles Symposium - IV. Unidade: ICMC
Subjects: VISÃO COMPUTACIONAL, REDES NEURAIS, IMAGEM
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
WATANABE, Thomio e WOLF, Denis Fernando. Instance segmentation as image segmentation annotation. 2019, Anais.. Piscataway: IEEE, 2019. Disponível em: https://doi.org/10.1109/IVS.2019.8814026. Acesso em: 27 nov. 2025.
APA
Watanabe, T., & Wolf, D. F. (2019). Instance segmentation as image segmentation annotation. In Proceedings. Piscataway: IEEE. doi:10.1109/IVS.2019.8814026
NLM
Watanabe T, Wolf DF. Instance segmentation as image segmentation annotation [Internet]. Proceedings. 2019 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/IVS.2019.8814026
Vancouver
Watanabe T, Wolf DF. Instance segmentation as image segmentation annotation [Internet]. Proceedings. 2019 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/IVS.2019.8814026
Trabalho de evento
Verisimilar percept sequences tests for autonomous driving intelligent agent assessment (2018)
Watanabe, Thomio; Wolf, Denis Fernando
Source: Proceedings. Conference titles: Latin American Robotic Symposium - LARS. Unidade: ICMC
Subjects: VEÍCULOS AUTÔNOMOS, ROBÓTICA, VISÃO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
WATANABE, Thomio e WOLF, Denis Fernando. Verisimilar percept sequences tests for autonomous driving intelligent agent assessment. 2018, Anais.. Los Alamitos: IEEE, 2018. Disponível em: https://doi.org/10.1109/LARS/SBR/WRE.2018.00048. Acesso em: 27 nov. 2025.
APA
Watanabe, T., & Wolf, D. F. (2018). Verisimilar percept sequences tests for autonomous driving intelligent agent assessment. In Proceedings. Los Alamitos: IEEE. doi:10.1109/LARS/SBR/WRE.2018.00048
NLM
Watanabe T, Wolf DF. Verisimilar percept sequences tests for autonomous driving intelligent agent assessment [Internet]. Proceedings. 2018 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/LARS/SBR/WRE.2018.00048
Vancouver
Watanabe T, Wolf DF. Verisimilar percept sequences tests for autonomous driving intelligent agent assessment [Internet]. Proceedings. 2018 ;[citado 2025 nov. 27 ] Available from: https://doi.org/10.1109/LARS/SBR/WRE.2018.00048

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