2D and 3D Palmprint and Palm Vein Recognition Based on Neural Architecture Search

doi:10.1007/s11633-021-1292-1

CASIA OpenIR > 学术期刊 > Machine Intelligence Research

	2D and 3D Palmprint and Palm Vein Recognition Based on Neural Architecture Search
	Wei Jia 1,2; Wei Xia 1,2; Yang Zhao1,2 ; Hai Min 1,2; Yan-Xiang Chen 1,2
发表期刊	International Journal of Automation and Computing
ISSN	1476-8186
	2021
卷号	18 期号:3 页码:377-409
摘要	Palmprint 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. In recent years, in the field of artificial intelligence, deep learning has gradually become the mainstream recognition technology because of its excellent recognition performance. Some researchers have tried to use convolutional neural networks (CNNs) for palmprint recognition and palm vein recognition. However, the architectures of these CNNs have mostly been developed manually by human experts, which is a time-consuming and error-prone process. In order to overcome some shortcomings of manually designed CNN, neural architecture search (NAS) technology has become an important research direction of deep learning. The significance of NAS is to solve the deep learning model′s parameter adjustment problem, which is a cross-study combining optimization and machine learning. NAS technology represents the future development direction of deep learning. However, up to now, NAS technology has not been well studied for palmprint recognition and palm vein recognition. In this paper, in order to investigate the problem of NAS-based 2D and 3D palmprint recognition and palm vein recognition in-depth, we conduct a performance evaluation of twenty representative NAS methods on five 2D palmprint databases, two palm vein databases, and one 3D palmprint database. Experimental results show that some NAS methods can achieve promising recognition results. Remarkably, among different evaluated NAS methods, ProxylessNAS achieves the best recognition performance.
关键词	Performance evaluation neural architecture search biometrics palmprint palm vein deep learning
DOI	10.1007/s11633-021-1292-1
引用统计	被引频次：14[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/44289
专题	学术期刊_Machine Intelligence Research
作者单位	1.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
推荐引用方式 GB/T 7714	Wei Jia,Wei Xia,Yang Zhao,et al. 2D and 3D Palmprint and Palm Vein Recognition Based on Neural Architecture Search[J]. International Journal of Automation and Computing,2021,18(3):377-409.
APA	Wei Jia,Wei Xia,Yang Zhao,Hai Min,&Yan-Xiang Chen.(2021).2D and 3D Palmprint and Palm Vein Recognition Based on Neural Architecture Search.International Journal of Automation and Computing,18(3),377-409.
MLA	Wei Jia,et al."2D and 3D Palmprint and Palm Vein Recognition Based on Neural Architecture Search".International Journal of Automation and Computing 18.3(2021):377-409.

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