SDBM: Supervised Decision Boundary Maps for machine learning classifiers (2022)
- Authors:
- USP affiliated authors: HIRATA JUNIOR, ROBERTO - IME ; OLIVEIRA, ARTUR ANDRÉ ALMEIDA DE MACEDO - IME ; ESPADOTO, MATEUS - IME
- Unidade: IME
- DOI: 10.5220/0010896200003124
- Assunto: APRENDIZADO COMPUTACIONAL
- Keywords: Dimensionality Reduction; Dense Maps
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: SciTePress
- Publisher place: Lisboa
- Date published: 2022
- Source:
- Título: Proceedings
- Conference titles: International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - IVAPP
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: hybrid
- Licença: cc-by-nc-nd
-
ABNT
OLIVEIRA, Artur André Almeida de Macedo et al. SDBM: Supervised Decision Boundary Maps for machine learning classifiers. 2022, Anais.. Lisboa: SciTePress, 2022. Disponível em: https://doi.org/10.5220/0010896200003124. Acesso em: 27 dez. 2025. -
APA
Oliveira, A. A. A. de M., Espadoto, M., Hirata Júnior, R., & Telea, A. C. (2022). SDBM: Supervised Decision Boundary Maps for machine learning classifiers. In Proceedings. Lisboa: SciTePress. doi:10.5220/0010896200003124 -
NLM
Oliveira AAA de M, Espadoto M, Hirata Júnior R, Telea AC. SDBM: Supervised Decision Boundary Maps for machine learning classifiers [Internet]. Proceedings. 2022 ;[citado 2025 dez. 27 ] Available from: https://doi.org/10.5220/0010896200003124 -
Vancouver
Oliveira AAA de M, Espadoto M, Hirata Júnior R, Telea AC. SDBM: Supervised Decision Boundary Maps for machine learning classifiers [Internet]. Proceedings. 2022 ;[citado 2025 dez. 27 ] Available from: https://doi.org/10.5220/0010896200003124 - Improving self-supervised dimensionality reduction: exploring hyperparameters and pseudo-labeling strategies
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Informações sobre o DOI: 10.5220/0010896200003124 (Fonte: oaDOI API)
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