Contextual spaces re-ranking : accelerating the re-sort ranked lists step on heterogeneous systems
Flávia Pisani, Daniel C. G. Pedronette, Ricardo da S. Torres, Edson Borin
ARTIGO
Inglês
Re‐ranking algorithms have been proposed to improve the effectiveness of content‐based image retrieval systems by exploiting contextual information encoded in distance measures and ranked lists. In this paper, we show how we improved the efficiency of one
FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP
2013/08645-0
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ
306580/2012-8; 484254/2012-0
COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPES
Fechado
Contextual spaces re-ranking : accelerating the re-sort ranked lists step on heterogeneous systems
Flávia Pisani, Daniel C. G. Pedronette, Ricardo da S. Torres, Edson Borin
Contextual spaces re-ranking : accelerating the re-sort ranked lists step on heterogeneous systems
Flávia Pisani, Daniel C. G. Pedronette, Ricardo da S. Torres, Edson Borin
Fontes
|
Concurrency and computation: practice and experience Vol. 29, no. 22 (2017), n. art. e3962 |