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Journals >
Laser & Optoelectronics Progress >
Volume 58 >
Issue 20 >
Page 2010002 > Article
Laser & Optoelectronics Progress
Vol. 58, Issue 20, 2010002 (2021)
Finger Vein Recognition Based on Improved ResNet
Kaixuan Wang
1、*
, Guanghua Chen
1、2
, and Hongjia Chu
1
Author Affiliations
1
Microelectronics R&D Center, Shanghai University, Shanghai 200444, China;
2
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China
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DOI:
10.3788/LOP202158.2010002
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Kaixuan Wang, Guanghua Chen, Hongjia Chu. Finger Vein Recognition Based on Improved ResNet[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2010002
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Fig. 1.
Residual block
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Fig. 2.
Conventional convolution
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Fig. 3.
Depthwise convolution
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Fig. 4.
Depthwise over-parameterized convolution
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Fig. 5.
Structure of dual attention mechanism
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Fig. 6.
Improved residual block
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Fig. 7.
Improved ResNet
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Fig. 8.
Test accuracy. (a) FV-USM;(b) SDUMLA
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Method
Accuracy /%
Time /ms
Parameter
FV-USM
SDUMLA
FV-USM
SDUMLA
VGG-16
95.8333
95.7721
49
49
44.0×10
6
DenseNet
96.9512
98.1618
34
34
8.5×10
6
AlexNet
92.2764
96.3235
16
16
26.7×10
6
ResNet-18
96.0366
97.7941
16
16
19.7×10
6
Improved ResNet+DO-Conv
98.4756
98.7132
15
15
14.8×10
6
Improved ResNet+DO-Conv+LSCE
99.0854
98.8971
15
15
14.8×10
6
Improved ResNet+DO-Conv+LSCE+(SE+SAM)
99.4919
99.4485
15
15
14.8×10
6
Table 1.
Comparison of structure and performance indicators of different models
Abstract
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Kaixuan Wang, Guanghua Chen, Hongjia Chu. Finger Vein Recognition Based on Improved ResNet[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2010002
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Paper Information
Category: Image Processing
Received: Nov. 30, 2020
Accepted: Jan. 2, 2021
Published Online: Oct. 13, 2021
The Author Email: Wang Kaixuan (18361258215@163.com)
DOI:
10.3788/LOP202158.2010002
Recommended Topics
laser devices and laser physics
Lasers and Laser Optics
Laser physics
laser manufacturing
Instrumentation, Measurement and Metrology
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