Finger Vein Verification Algorithm Based on Fully Convolutional Neural Network and Conditional Random Field

Owing to the complexity of finger vein patterns in shape and spatial dependence, the existing methods suffer from an inability to obtain accurate and stable finger vein features. This paper, so as to compensate this defect, proposes an end-to-end model to extract vein textures through integrating th...

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Vydané v:	IEEE access Ročník 8; s. 65402 - 65419
Hlavní autori:	Zeng, Junying, Wang, Fan, Deng, Jianxiang, Qin, Chuanbo, Zhai, Yikui, Gan, Junying, Piuri, Vincenzo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Artificial neural networks Back propagation networks Complexity Conditional random fields Convolution Convolutional neural networks CRF FCN Feature extraction finger-vein verification Formability Image segmentation Neural networks Recurrent neural networks Training U-Net Veins Veins & arteries Verification
ISSN:	2169-3536, 2169-3536
On-line prístup:	Získať plný text
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