Research on finger vein recognition based on capsule network
This paper propose a finger vein recognition algorithm based on the CapsNets(Capsule Network for short) to solve the problem of the information loss of the finger vein in the Convolution Neural Network(CNN). The CapsNets is transferred from the bottom to the high level in the form of capsule in the...
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Format: | Article |
Language: | zho |
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National Computer System Engineering Research Institute of China
2018-10-01
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Series: | Dianzi Jishu Yingyong |
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Online Access: | http://www.chinaaet.com/article/3000091554 |
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author | Yu Chengbo Xiong Dien |
author_facet | Yu Chengbo Xiong Dien |
author_sort | Yu Chengbo |
collection | DOAJ |
description | This paper propose a finger vein recognition algorithm based on the CapsNets(Capsule Network for short) to solve the problem of the information loss of the finger vein in the Convolution Neural Network(CNN). The CapsNets is transferred from the bottom to the high level in the form of capsule in the whole learning process, so that the multidimensional characteristics of the finger vein are encapsulated in the form of vector, and the features will be preserved in the network, but not in the network after the loss is recovered. In this paper, 60 000 images are used as training set, and 10 000 images are used as test set. The experimental results show that the network structure features of CapsNets are more obvious than that of CNN, the accuracy of VGG is increased by 13.6%, and the value of loss converges to 0.01. |
first_indexed | 2024-12-11T00:39:11Z |
format | Article |
id | doaj.art-0e5bcf8a6ec24708b7bf3dcb84378bf6 |
institution | Directory Open Access Journal |
issn | 0258-7998 |
language | zho |
last_indexed | 2024-12-11T00:39:11Z |
publishDate | 2018-10-01 |
publisher | National Computer System Engineering Research Institute of China |
record_format | Article |
series | Dianzi Jishu Yingyong |
spelling | doaj.art-0e5bcf8a6ec24708b7bf3dcb84378bf62022-12-22T01:27:00ZzhoNational Computer System Engineering Research Institute of ChinaDianzi Jishu Yingyong0258-79982018-10-014410151810.16157/j.issn.0258-7998.1822363000091554Research on finger vein recognition based on capsule networkYu Chengbo0Xiong Dien1School of Electrical and Electronic Engineering,Chongqing University of Techology,Chongqing 400050,ChinaSchool of Electrical and Electronic Engineering,Chongqing University of Techology,Chongqing 400050,ChinaThis paper propose a finger vein recognition algorithm based on the CapsNets(Capsule Network for short) to solve the problem of the information loss of the finger vein in the Convolution Neural Network(CNN). The CapsNets is transferred from the bottom to the high level in the form of capsule in the whole learning process, so that the multidimensional characteristics of the finger vein are encapsulated in the form of vector, and the features will be preserved in the network, but not in the network after the loss is recovered. In this paper, 60 000 images are used as training set, and 10 000 images are used as test set. The experimental results show that the network structure features of CapsNets are more obvious than that of CNN, the accuracy of VGG is increased by 13.6%, and the value of loss converges to 0.01.http://www.chinaaet.com/article/3000091554capsnetsfinger vein recognitiondeep learningcnn |
spellingShingle | Yu Chengbo Xiong Dien Research on finger vein recognition based on capsule network Dianzi Jishu Yingyong capsnets finger vein recognition deep learning cnn |
title | Research on finger vein recognition based on capsule network |
title_full | Research on finger vein recognition based on capsule network |
title_fullStr | Research on finger vein recognition based on capsule network |
title_full_unstemmed | Research on finger vein recognition based on capsule network |
title_short | Research on finger vein recognition based on capsule network |
title_sort | research on finger vein recognition based on capsule network |
topic | capsnets finger vein recognition deep learning cnn |
url | http://www.chinaaet.com/article/3000091554 |
work_keys_str_mv | AT yuchengbo researchonfingerveinrecognitionbasedoncapsulenetwork AT xiongdien researchonfingerveinrecognitionbasedoncapsulenetwork |