Structural Feature Measurement Using Fast VO Model for Blurred Palmprint Recognition

Author(s):  
Gang Wang ◽  
Weibo Wei ◽  
Zhenkuan Pan ◽  
Danfeng Hong ◽  
Mengqi Jia
2013 ◽  
Vol 40 (7) ◽  
pp. 668
Author(s):  
Wei-Min GAO ◽  
Yan LI ◽  
Shu-Wei ZHANG ◽  
Ling YANG

Author(s):  
Wei Jia ◽  
Wei Xia ◽  
Yang Zhao ◽  
Hai Min ◽  
Yan-Xiang Chen

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. 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.


2021 ◽  
pp. 073527512110299
Author(s):  
Jeremy E. Fiel

This article builds a framework for a relational approach to segregation that emphasizes structures of interactions, transactions, and ties between and within social categories. Rather than explaining segregation with dominants imposing formal rules or homophilic people sorting themselves, I highlight segregation’s emergence amid dueling control efforts among actors with malleable categorical identities. And rather than assuming segregation necessarily fuels cycles of inequality or persecution, I identify nuanced advantages and disadvantages for different actors in social conflict. I also explore an underappreciated role of institutions in segregation: They guide relations across different domains of activity that may have different degrees of segregation. An overarching theme is that segregation is not a specific thing with regular causes and effects but an inherently contradictory structural feature of relations that evolves as actors struggle for control.


1970 ◽  
Vol 23 (11) ◽  
pp. 569-571 ◽  
Author(s):  
JUN''ICHI SHOJI ◽  
YUZO NAKAGAWA
Keyword(s):  

Author(s):  
Lunke Fei ◽  
Jianyang Qin ◽  
Peng Liu ◽  
Jie Wen ◽  
Chunwei Tian ◽  
...  

2011 ◽  
Vol 32 (3) ◽  
pp. 217-223 ◽  
Author(s):  
Shigenori Ito ◽  
Takashi Nakahari ◽  
Daisuke Yamamoto

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