Laser & Optoelectronics Progress, Vol. 57, Issue 8, 081005 (2020)
Finger Vein Recognition Based on Improved AlexNet
Tao Zhiyong1, Hu Yalei1,2,*, and Lin Sen1
- 1School of Electronic & Information Engineering, Liaoning Technical University, Huludao, Liaoning 125105, China;
- 2Fuxinlixing Technology Company Limited, Fuxin, Liaoning 123000, China
An improved AlexNet structure is proposed to solve the problem of long time and low recognition accuracy of an AlexNet training finger vein recognition system. To address the problem of limited image size and poor adaptability of an AlexNet network model, the network structure of spatial pyramid pooling mode is introduced. To fasten the network’s training speed and reduce the complexity of the network model, the convolution kernel size of AlexNet, network depth, and the full connection layer are adjusted. Results show that the improved network model has a significant improvement on the recognition accuracy and training duration compared with the AlexNet model in both public and private finger vein datasets.
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