A new interpretable unsupervised anomaly detection method based on residual explanation (2022)
Source: IEEE Access. Unidade: EP
Subjects: APRENDIZAGEM PROFUNDA, FALHA, TOMADA DE DECISÃO
ABNT
OLIVEIRA, David Fernandes Neves et al. A new interpretable unsupervised anomaly detection method based on residual explanation. IEEE Access, v. 10, p. 1401-1409, 2022Tradução . . Disponível em: https://www.doi.org/10.1109/ACCESS.2021.3137633. Acesso em: 06 out. 2024.APA
Oliveira, D. F. N., Vismari, L. F., Nascimento, A. M., Almeida Junior, J. R. de, Cugnasca, P. S., Camargo Júnior, J. B., et al. (2022). A new interpretable unsupervised anomaly detection method based on residual explanation. IEEE Access, 10, 1401-1409. doi:10.1109/ACCESS.2021.3137633NLM
Oliveira DFN, Vismari LF, Nascimento AM, Almeida Junior JR de, Cugnasca PS, Camargo Júnior JB, Almeida L de, Gripp R, Neves M. A new interpretable unsupervised anomaly detection method based on residual explanation [Internet]. IEEE Access. 2022 ; 10 1401-1409.[citado 2024 out. 06 ] Available from: https://www.doi.org/10.1109/ACCESS.2021.3137633Vancouver
Oliveira DFN, Vismari LF, Nascimento AM, Almeida Junior JR de, Cugnasca PS, Camargo Júnior JB, Almeida L de, Gripp R, Neves M. A new interpretable unsupervised anomaly detection method based on residual explanation [Internet]. IEEE Access. 2022 ; 10 1401-1409.[citado 2024 out. 06 ] Available from: https://www.doi.org/10.1109/ACCESS.2021.3137633