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基于改进MobileNet的指静脉识别算法

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指静脉处于手指皮肤里层不易改变,利用指静脉进行身份识别与验证已经成为生物识别领域的一个研究热点.基于CNN的指静脉识别参数量大、计算量大、运行时间长.针对这些问题,论文提出一种基于改进轻量级网络(Mo-bileNet)的指静脉识别算法.改进后的网络融入粒子群算法(PSO)对MobileNet参数进行优化.实验结果表明,该识别算法在保持高精度的前提下,减少了参数量和运算时间.
Finger Vein Recognition Algorithm Based on Improved MobileNet
Finger vein is located in the inner layer of finger skin and is not easy to change.Using finger vein for identity recog-nition and verification has become a research hotspot in the field of biometrics.The finger vein recognition based on CNN has large amount of parameters,large amount of calculation and long running time.To solve these problems,this paper proposes a finger vein recognition algorithm based on improved lightweight network(MobileNet).The improved network integrates particle swarm optimiza-tion(PSO)to optimize the parameters of MobileNet.Experimental results show that the recognition algorithm reduces the amount of parameters and operation time on the premise of maintaining high accuracy.

deep learningfinger vein recognitionMobileNetPSO

孙俐、高尚

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江苏科技大学计算机学院 镇江 212100

深度学习 指静脉识别 轻量级网络 粒子群算法

2024

计算机与数字工程
中国船舶重工集团公司第七0九研究所

计算机与数字工程

CSTPCD
影响因子:0.355
ISSN:1672-9722
年,卷(期):2024.52(7)