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Artigo de periodico
A comprehensive review of deep learning techniques for interaction-aware trajectory prediction in urban autonomous driving (2025)
Gomes, Iago Pachêco ; Wolf, Denis Fernando
Fonte: Neurocomputing. Unidade: ICMC
Assuntos: VEÍCULOS AUTÔNOMOS, MÉTODOS DE PREVISÃO E CORREÇÃO, TRAJETÓRIA, TOMADA DE DECISÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GOMES, Iago Pachêco e WOLF, Denis Fernando. A comprehensive review of deep learning techniques for interaction-aware trajectory prediction in urban autonomous driving. Neurocomputing, v. 651, p. 1-19, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2025.131014. Acesso em: 22 nov. 2025.
APA
Gomes, I. P., & Wolf, D. F. (2025). A comprehensive review of deep learning techniques for interaction-aware trajectory prediction in urban autonomous driving. Neurocomputing, 651, 1-19. doi:10.1016/j.neucom.2025.131014
NLM
Gomes IP, Wolf DF. A comprehensive review of deep learning techniques for interaction-aware trajectory prediction in urban autonomous driving [Internet]. Neurocomputing. 2025 ; 651 1-19.[citado 2025 nov. 22 ] Available from: https://doi.org/10.1016/j.neucom.2025.131014
Vancouver
Gomes IP, Wolf DF. A comprehensive review of deep learning techniques for interaction-aware trajectory prediction in urban autonomous driving [Internet]. Neurocomputing. 2025 ; 651 1-19.[citado 2025 nov. 22 ] Available from: https://doi.org/10.1016/j.neucom.2025.131014
Artigo de periodico
Transduction to induction: unsupervised representation learning based on rank information (2025)
Biotto, Deryk Willyan ; Valem, Lucas Pascotti ; Pedronette, Daniel Carlos Guimarães ; Salvadeo, Denis Henrique Pinheiro
Fonte: Neurocomputing. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, RECONHECIMENTO DE IMAGEM, RECUPERAÇÃO DA INFORMAÇÃO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BIOTTO, Deryk Willyan et al. Transduction to induction: unsupervised representation learning based on rank information. Neurocomputing, v. 651, p. 1-12, 2025Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2025.131010. Acesso em: 22 nov. 2025.
APA
Biotto, D. W., Valem, L. P., Pedronette, D. C. G., & Salvadeo, D. H. P. (2025). Transduction to induction: unsupervised representation learning based on rank information. Neurocomputing, 651, 1-12. doi:10.1016/j.neucom.2025.131010
NLM
Biotto DW, Valem LP, Pedronette DCG, Salvadeo DHP. Transduction to induction: unsupervised representation learning based on rank information [Internet]. Neurocomputing. 2025 ; 651 1-12.[citado 2025 nov. 22 ] Available from: https://doi.org/10.1016/j.neucom.2025.131010
Vancouver
Biotto DW, Valem LP, Pedronette DCG, Salvadeo DHP. Transduction to induction: unsupervised representation learning based on rank information [Internet]. Neurocomputing. 2025 ; 651 1-12.[citado 2025 nov. 22 ] Available from: https://doi.org/10.1016/j.neucom.2025.131010
Artigo de periodico
Learning label diffusion maps for semi-automatic segmentation of lung CT images with COVID-19 (2023)
Bruzadin, Aldimir; Boaventura, Maurílio ; Colnago, Marilaine ; Negri, Rogério Galante ; Casaca, Wallace Correa de Oliveira
Fonte: Neurocomputing. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, PROCESSAMENTO DE IMAGENS, DIAGNÓSTICO POR IMAGEM, TOMOGRAFIA, COVID-19
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BRUZADIN, Aldimir et al. Learning label diffusion maps for semi-automatic segmentation of lung CT images with COVID-19. Neurocomputing, v. 522, p. 24-38, 2023Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2022.12.003. Acesso em: 22 nov. 2025.
APA
Bruzadin, A., Boaventura, M., Colnago, M., Negri, R. G., & Casaca, W. C. de O. (2023). Learning label diffusion maps for semi-automatic segmentation of lung CT images with COVID-19. Neurocomputing, 522, 24-38. doi:10.1016/j.neucom.2022.12.003
NLM
Bruzadin A, Boaventura M, Colnago M, Negri RG, Casaca WC de O. Learning label diffusion maps for semi-automatic segmentation of lung CT images with COVID-19 [Internet]. Neurocomputing. 2023 ; 522 24-38.[citado 2025 nov. 22 ] Available from: https://doi.org/10.1016/j.neucom.2022.12.003
Vancouver
Bruzadin A, Boaventura M, Colnago M, Negri RG, Casaca WC de O. Learning label diffusion maps for semi-automatic segmentation of lung CT images with COVID-19 [Internet]. Neurocomputing. 2023 ; 522 24-38.[citado 2025 nov. 22 ] Available from: https://doi.org/10.1016/j.neucom.2022.12.003
Artigo de periodico
Leveraging convergence behavior to balance conflicting tasks in multitask learning (2022)
Nakamura, Angelica Tiemi Mizuno ; Grassi Júnior, Valdir ; Wolf, Denis Fernando
Fonte: Neurocomputing. Unidade: ICMC
Assuntos: APRENDIZADO COMPUTACIONAL, REDES NEURAIS, ANÁLISE DE DESEMPENHO
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: 22 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. 22 ] 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. 22 ] Available from: https://doi.org/10.1016/j.neucom.2022.09.042
Artigo de periodico
Effects of burst-timing-dependent plasticity on synchronous behaviour in neuronal network (2021)
Silveira, João Antonio Paludo; Protachevicz, R. P. ; Viana, Ricardo Luiz; Batista, Antonio
Fonte: Neurocomputing. Unidade: IF
Assuntos: BIOFÍSICA, REDES NEURAIS, NEURÔNIOS, SINCRONIZAÇÃO, SINAPSE, PLASTICIDADE NEURONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SILVEIRA, João Antonio Paludo et al. Effects of burst-timing-dependent plasticity on synchronous behaviour in neuronal network. Neurocomputing, v. 436, p. 126-135, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.neucom.2021.01.044. Acesso em: 22 nov. 2025.
APA
Silveira, J. A. P., Protachevicz, R. P., Viana, R. L., & Batista, A. (2021). Effects of burst-timing-dependent plasticity on synchronous behaviour in neuronal network. Neurocomputing, 436, 126-135. doi:10.1016/j.neucom.2021.01.044
NLM
Silveira JAP, Protachevicz RP, Viana RL, Batista A. Effects of burst-timing-dependent plasticity on synchronous behaviour in neuronal network [Internet]. Neurocomputing. 2021 ; 436 126-135.[citado 2025 nov. 22 ] Available from: https://doi.org/10.1016/j.neucom.2021.01.044
Vancouver
Silveira JAP, Protachevicz RP, Viana RL, Batista A. Effects of burst-timing-dependent plasticity on synchronous behaviour in neuronal network [Internet]. Neurocomputing. 2021 ; 436 126-135.[citado 2025 nov. 22 ] Available from: https://doi.org/10.1016/j.neucom.2021.01.044

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