On novelty detection for multi-class classification using non-linear metric learning (2021)
- Authors:
- USP affiliated authors: PAIVA NETO, AFONSO - ICMC ; SILVA, SAMUEL ROCHA - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.eswa.2020.114193
- Subjects: ALGORITMOS; APRENDIZAGEM
- Keywords: Novelty detection; Outlier detection; Anomaly detection; Metric learning; Multi-class classification
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Expert Systems With Applications
- ISSN: 0957-4174
- Volume/Número/Paginação/Ano: v. 167, p. 1-12, 2021
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
SILVA, Samuel Rocha et al. On novelty detection for multi-class classification using non-linear metric learning. Expert Systems With Applications, v. 167, p. 1-12, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.eswa.2020.114193. Acesso em: 03 jun. 2024. -
APA
Silva, S. R., Vieira, T., Martínez, D., & Paiva, A. (2021). On novelty detection for multi-class classification using non-linear metric learning. Expert Systems With Applications, 167, 1-12. doi:10.1016/j.eswa.2020.114193 -
NLM
Silva SR, Vieira T, Martínez D, Paiva A. On novelty detection for multi-class classification using non-linear metric learning [Internet]. Expert Systems With Applications. 2021 ; 167 1-12.[citado 2024 jun. 03 ] Available from: https://doi.org/10.1016/j.eswa.2020.114193 -
Vancouver
Silva SR, Vieira T, Martínez D, Paiva A. On novelty detection for multi-class classification using non-linear metric learning [Internet]. Expert Systems With Applications. 2021 ; 167 1-12.[citado 2024 jun. 03 ] Available from: https://doi.org/10.1016/j.eswa.2020.114193 - A user-friendly interactive framework for unsteady fluid flow segmentation and visualization
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Informações sobre o DOI: 10.1016/j.eswa.2020.114193 (Fonte: oaDOI API)
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