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

Daniel Carlos Guimarães Pedronette, Jurandy Almeida, Ricardo da S. Torres

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

FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP

COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES

Fechado

A graph-based ranked-list model for unsupervised distance learning on shape retrieval

Daniel Carlos Guimarães Pedronette, Jurandy Almeida, Ricardo da S. Torres


										

A graph-based ranked-list model for unsupervised distance learning on shape retrieval

Daniel Carlos Guimarães Pedronette, Jurandy Almeida, Ricardo da S. Torres

    Fontes

    Pattern recognition letters

    Vol. 83, pt 3 (Nov., 2016), p. 357-367