Contextual spaces re-ranking : accelerating the re-sort ranked lists step on heterogeneous systems

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

CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ

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