A graph-based ranked-list model for unsupervised distance learning on shape retrieval
ARTIGO
Inglês
Agradecimentos: The authors are grateful to São Paulo Research Foundation - FAPESP (grants 2013/08645-0 and 2013/50169-1), CNPq (grants 306580/2012-8 and 484254/2012-0), CAPES, AMD, and Microsoft Research.
Several re-ranking algorithms have been proposed recently. Some effective approaches are based on complex graph-based diffusion processes, which usually are time consuming and therefore inappropriate for real-world large scale shape collections. In this p
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ
306580/2012-8; 484254/2012-0
FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP
2013/08645-0; 2013/50169-1
COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES
Fechado
A graph-based ranked-list model for unsupervised distance learning on shape retrieval
A graph-based ranked-list model for unsupervised distance learning on shape retrieval
Fontes
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Pattern recognition letters Vol. 83, pt 3 (Nov., 2016), p. 357-367 |