Eficácia, Eficiência e Escalabilidade em Método de Aprendizado Não Supervisionado de Busca de Imagens

• Lucas Valem UNESP
• Daniel Pedronette UNESP

Abstract

Various unsupervised learning methods have been proposed obtaining significant improvements in the effectiveness of image search systems. However, despite the relevant effectiveness gains, these approaches commonly require high computation efforts, not addressing properly efficiency and scalability requirements. In this scientific initiation work, we present a novel unsupervised learning approach which achieves significant effectiveness gains considering both efficiency and scalability requirements. Parallel and heterogeneous computing, using CPU and GPU devices, were exploited.

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