Handwritten data clustering using agents competition in networks (2013)
- Authors:
- Autor USP: LIANG, ZHAO - ICMC
- Unidade: ICMC
- DOI: 10.1007/s10851-012-0353-z
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Source:
- Título: Journal of Mathematical Imaging and Vision
- ISSN: 0924-9907
- Volume/Número/Paginação/Ano: v. 45, n. 3, p. 264-276, mar. 2013
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
SILVA, Thiago C e LIANG, Zhao e CUPERTINO, Thiago H. Handwritten data clustering using agents competition in networks. Journal of Mathematical Imaging and Vision, v. 45, n. 3, p. 264-276, 2013Tradução . . Disponível em: https://doi.org/10.1007/s10851-012-0353-z. Acesso em: 09 jan. 2026. -
APA
Silva, T. C., Liang, Z., & Cupertino, T. H. (2013). Handwritten data clustering using agents competition in networks. Journal of Mathematical Imaging and Vision, 45( 3), 264-276. doi:10.1007/s10851-012-0353-z -
NLM
Silva TC, Liang Z, Cupertino TH. Handwritten data clustering using agents competition in networks [Internet]. Journal of Mathematical Imaging and Vision. 2013 ; 45( 3): 264-276.[citado 2026 jan. 09 ] Available from: https://doi.org/10.1007/s10851-012-0353-z -
Vancouver
Silva TC, Liang Z, Cupertino TH. Handwritten data clustering using agents competition in networks [Internet]. Journal of Mathematical Imaging and Vision. 2013 ; 45( 3): 264-276.[citado 2026 jan. 09 ] Available from: https://doi.org/10.1007/s10851-012-0353-z - Data heterogeneity consideration in semi-supervised learning
- Machine learning via dynamical processes in complex networks
- Semi-supervised learning guided by the modularity measure in complex networks
- Handwritten digits recognition using a high level network-based approach
- On the data classification using complex network entropy
- Caracterização de classes via otimização em redes complexas
- Network-based supervised data classification by using an heuristic of ease of access
- Label propagation through neuronal synchrony
- QK-means: a clustering technique based on community detection and 'capa'-means for deployment of custer head nodes
- Attraction forces based semi-supervised learning
Informações sobre o DOI: 10.1007/s10851-012-0353-z (Fonte: oaDOI API)
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