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Trabalho de evento
Constructive interpretability with colabel: corroborative integration, complementary features, and collaborative learning (2022)
Suprem, Abhijit; Vaidya, Sanjyot; Cherkadi, Suma; Singh, Purva; Ferreira, João Eduardo ; Pu, Calton
Source: Proceedings. Conference titles: International Conference on Cognitive Machine Intelligence - CogMI. Unidade: IME
Subjects: VISÃO COMPUTACIONAL, ENGENHARIA DE CONHECIMENTO, RECONHECIMENTO DE OBJETOS, VEÍCULOS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SUPREM, Abhijit et al. Constructive interpretability with colabel: corroborative integration, complementary features, and collaborative learning. 2022, Anais.. Piscataway: IEEE, 2022. Disponível em: https://doi.org/10.1109/CogMI56440.2022.00021. Acesso em: 07 nov. 2024.
APA
Suprem, A., Vaidya, S., Cherkadi, S., Singh, P., Ferreira, J. E., & Pu, C. (2022). Constructive interpretability with colabel: corroborative integration, complementary features, and collaborative learning. In Proceedings. Piscataway: IEEE. doi:10.1109/CogMI56440.2022.00021
NLM
Suprem A, Vaidya S, Cherkadi S, Singh P, Ferreira JE, Pu C. Constructive interpretability with colabel: corroborative integration, complementary features, and collaborative learning [Internet]. Proceedings. 2022 ;[citado 2024 nov. 07 ] Available from: https://doi.org/10.1109/CogMI56440.2022.00021
Vancouver
Suprem A, Vaidya S, Cherkadi S, Singh P, Ferreira JE, Pu C. Constructive interpretability with colabel: corroborative integration, complementary features, and collaborative learning [Internet]. Proceedings. 2022 ;[citado 2024 nov. 07 ] Available from: https://doi.org/10.1109/CogMI56440.2022.00021
Trabalho de evento
Evaluation of traditional and deep learning human detection techniques applied to surveillance: a performance comparison at distinct object sizes (2021)
Gonçalves, Vinicius Pereira ; Silva, Lourival Paulino da; Marques, Fátima de Lourdes dos Santos Nunes ; Ferreira, João Eduardo ; Araújo, Luciano Vieira de
Source: Proceedings. Conference titles: International Conference on Signal Processing, Communications and Computing. Unidades: EACH, IME
Subjects: PROCESSAMENTO DE SINAIS, VISÃO COMPUTACIONAL, APRENDIZAGEM PROFUNDA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
GONÇALVES, Vinicius Pereira et al. Evaluation of traditional and deep learning human detection techniques applied to surveillance: a performance comparison at distinct object sizes. 2021, Anais.. Piscataway: IEEE, 2021. Disponível em: https://doi.org/10.1109/ICSPCC52875.2021.9564442. Acesso em: 07 nov. 2024.
APA
Gonçalves, V. P., Silva, L. P. da, Marques, F. de L. dos S. N., Ferreira, J. E., & Araújo, L. V. de. (2021). Evaluation of traditional and deep learning human detection techniques applied to surveillance: a performance comparison at distinct object sizes. In Proceedings. Piscataway: IEEE. doi:10.1109/ICSPCC52875.2021.9564442
NLM
Gonçalves VP, Silva LP da, Marques F de L dos SN, Ferreira JE, Araújo LV de. Evaluation of traditional and deep learning human detection techniques applied to surveillance: a performance comparison at distinct object sizes [Internet]. Proceedings. 2021 ;[citado 2024 nov. 07 ] Available from: https://doi.org/10.1109/ICSPCC52875.2021.9564442
Vancouver
Gonçalves VP, Silva LP da, Marques F de L dos SN, Ferreira JE, Araújo LV de. Evaluation of traditional and deep learning human detection techniques applied to surveillance: a performance comparison at distinct object sizes [Internet]. Proceedings. 2021 ;[citado 2024 nov. 07 ] Available from: https://doi.org/10.1109/ICSPCC52875.2021.9564442
Artigo de periodico
ODIN: automated drift detection and recovery in video analytics (2020)
Suprem, Abhijit; Arulraj, Joy; Pu, Calton ; Ferreira, João Eduardo
Source: Proceedings of the VLDB Endowment. Unidade: IME
Assunto: VISÃO COMPUTACIONAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SUPREM, Abhijit et al. ODIN: automated drift detection and recovery in video analytics. Proceedings of the VLDB Endowment, v. 13, n. 12, p. 2453-2465, 2020Tradução . . Disponível em: https://doi.org/10.14778/3407790.3407837. Acesso em: 07 nov. 2024.
APA
Suprem, A., Arulraj, J., Pu, C., & Ferreira, J. E. (2020). ODIN: automated drift detection and recovery in video analytics. Proceedings of the VLDB Endowment, 13( 12), 2453-2465. doi:10.14778/3407790.3407837
NLM
Suprem A, Arulraj J, Pu C, Ferreira JE. ODIN: automated drift detection and recovery in video analytics [Internet]. Proceedings of the VLDB Endowment. 2020 ; 13( 12): 2453-2465.[citado 2024 nov. 07 ] Available from: https://doi.org/10.14778/3407790.3407837
Vancouver
Suprem A, Arulraj J, Pu C, Ferreira JE. ODIN: automated drift detection and recovery in video analytics [Internet]. Proceedings of the VLDB Endowment. 2020 ; 13( 12): 2453-2465.[citado 2024 nov. 07 ] Available from: https://doi.org/10.14778/3407790.3407837

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