CASIA OpenIR  > 学术期刊  > International Journal of Automation and Computing
A Performance Evaluation of Classic Convolutional Neural Networks for 2D and 3D Palmprint and Palm Vein Recognition
Wei Jia1,2; Jian Gao1,2; Wei Xia1,2; Yang Zhao1,2; Hai Min1,2; Jing-Ting Lu3
Source PublicationInternational Journal of Automation and Computing
ISSN1476-8186
2021
Volume18Issue:1Pages:18-44
AbstractPalmprint recognition and palm vein recognition are two emerging biometrics technologies. In the past two decades, many traditional methods have been proposed for palmprint recognition and palm vein recognition, and have achieved impressive results. However, the research on deep learning-based palmprint recognition and palm vein recognition is still very preliminary. In this paper, in order to investigate the problem of deep learning based 2D and 3D palmprint recognition and palm vein recognition in-depth, we conduct performance evaluation of seventeen representative and classic convolutional neural networks (CNNs) on one 3D palmprint database, five 2D palmprint databases and two palm vein databases. A lot of experiments have been carried out in the conditions of different network structures, different learning rates, and different numbers of network layers. We have also conducted experiments on both separate data mode and mixed data mode. Experimental results show that these classic CNNs can achieve promising recognition results, and the recognition performance of recently proposed CNNs is better. Particularly, among classic CNNs, one of the recently proposed classic CNNs, i.e., EfficientNet achieves the best recognition accuracy. However, the recognition performance of classic CNNs is still slightly worse than that of some traditional recognition methods.
KeywordPerformance evaluation convolutional neural network (CNN) biometrics palmprint palm vein deep learning
DOI10.1007/s11633-020-1257-9
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/42452
Collection学术期刊_International Journal of Automation and Computing
Affiliation1.School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230009, China
2.Anhui Province Key Laboratory of Industry Safety and Emergency Technology, Hefei 230009, China
3.Institution of Industry and Equipment Technology, Hefei University of Technology, Hefei 230009, China
Recommended Citation
GB/T 7714
Wei Jia,Jian Gao,Wei Xia,et al. A Performance Evaluation of Classic Convolutional Neural Networks for 2D and 3D Palmprint and Palm Vein Recognition[J]. International Journal of Automation and Computing,2021,18(1):18-44.
APA Wei Jia,Jian Gao,Wei Xia,Yang Zhao,Hai Min,&Jing-Ting Lu.(2021).A Performance Evaluation of Classic Convolutional Neural Networks for 2D and 3D Palmprint and Palm Vein Recognition.International Journal of Automation and Computing,18(1),18-44.
MLA Wei Jia,et al."A Performance Evaluation of Classic Convolutional Neural Networks for 2D and 3D Palmprint and Palm Vein Recognition".International Journal of Automation and Computing 18.1(2021):18-44.
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