Multimodal biometric recognition systems using deep learning based on the finger vein and finger knuckle print fusion-Reference-Cited by-同舟云学术

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Multimodal biometric recognition systems using deep learning based on the finger vein and finger knuckle print fusion

Published:2020-12 Issue:15 Volume:14 Page:3859-3868
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET image process

Author:

Daas Sara¹^ORCID,Yahi Amira¹,Bakir Toufik²,Sedhane Mouna¹,Boughazi Mohamed¹,Bourennane El‐Bay²

Affiliation:

1. Laboratory for Instrumentation and Communication Study and Research of annaba(LERICA)University Badji MokhtarBP12AnnabaAlgeria

2. Laboratory of Imaging and Artificial Vision(ImVia)University of Burgundy Franche‐Comte9 Av.Alain Savary, BP4787021078Dijon CedexFrance

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2020.0491

Reference48 articles.

1. Deep Learning in Biometrics

2. Incorporating iris, fingerprint and face biometric for fraud prevention in e‐passports using fuzzy vault

3. Manjunathswamy B. Thriveni J. Venugopal K. et al.: ‘Multi model personal authentication using finger vein and face images (mpaffi)’.2014 Int. Conf. on Parallel Distributed and Grid Computing Solan India 2014 pp.339–344

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4. Deep inner-knuckle-print recognition using lightweight Siamese network;Journal of Electronic Imaging;2024-08-02

5. Multimodal biometric authentication: A review;AI Communications;2024-05-16

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