OpenCL Implementations of a Genetic Algorithm for Feature Selection in Periocular Biometric Recognition

被引：0
|
作者：
Fazendeiro, Paulo [1 ]
Padole, Chandrashekhar [1 ]
Sequeira, Pedro [1 ]
Prata, Paula [1 ]
机构：
[1] Univ Beira Interior, Dept Informat, Inst Telecomunicacoes IT Portugal, Covilha, Portugal
来源：
SWARM, EVOLUTIONARY, AND MEMETIC COMPUTING, (SEMCCO 2012) | 2012年 / 7677卷
关键词：
GPGPU; Parallel Genetic Algorithms; Biometric Recognition; Periocular Recognition; OpenCL; Data Parallelism;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper explores OpenCL implementations of a genetic algorithm used to optimize the features vector in periocular biometric recognition. Using a multi core platform the algorithm is tested for CPU and GPU, exploring different parallelization levels for each operator of the genetic algorithm. The results show that using the GPU platform it is possible to accelerate the algorithm by several orders of magnitude, with a recognition rate similar to the one obtained in the sequential version. The results also show that it is possible to use only a small portion of the features without any degradation of the classifier's recognition rate.
引用
收藏
页码：729 / 737
页数：9
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