Multimodal biometric identification: leveraging convolutional neural network (CNN) architectures and fusion techniques with fingerprint and finger vein data

被引：0

作者：

Alshardan, Amal ^{[1
]}

Kumar, Arun ^{[2
]}

Alghamdi, Mohammed ^{[3
]}

Maashi, Mashael ^{[4
]}

Alahmari, Saad ^{[5
]}

Alharbi, Abeer A.K. ^{[6
]}

Almukadi, Wafa ^{[7
]}

Alzahrani, Yazeed ^{[8
]}

机构：

[1] Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Riyadh, Saudi Arabia

[2] Department of Computer Science & Engineering, G.L Bajaj Institute of Technology and Management, Gr. Noida, India

[3] Department of Information Systems, College of Computer Science, King Khalid University, Asir, Abha, Saudi Arabia

[4] Department of Software Engineering, College of Computer and Information Sciences, King Saud University, Riyadh, Riyadh, Saudi Arabia

[5] Department of Computer Science, Applied College, Northern Border University, Northern Borders, Arar, Saudi Arabia

[6] Department of Information Systems, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University, Riyadh, Riyadh, Saudi Arabia

[7] Department of Software Engineering, College of Engineering and Computer Science, University of Jeddah, Makkah, Jeddah, Saudi Arabia

[8] Department of Computer Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Wadi Addawasir, Riyadh, Saudi Arabia

来源：

PeerJ Computer Science | 2024年 / 10卷

关键词：

Authentication - Contrastive Learning - Deep neural networks - Equalizers - Image enhancement - Image fusion - Multilayer neural networks - Palmprint recognition - Time difference of arrival;

D O I：

10.7717/PEERJ-CS.2440

中图分类号：

学科分类号：

摘要：

引用

共 30 条

[1] Multimodal biometric identification : leveraging convolutional neural network (CNN) architectures and fusion techniques with fi ngerprint and fi nger vein data
Alshardan, Amal
Kumar, Arun
Alghamdi, Mohammed
Maashi, Mashael
Alahmari, Saad
Alharbi, Abeer A. K.
Almukadi, Wafa
Alzahrani, Yazeed
PEERJ COMPUTER SCIENCE, 2024, 10
[2] Convolutional neural networks approach for multimodal biometric identification system using the fusion of fingerprint, finger-vein and face images
Cherrat, El Mehdi
Alaoui, Rachid
Bouzahir, Hassane
PEERJ COMPUTER SCIENCE, 2020, 2020 (01) : 1 - 15
[3] Convolutional Neural Network Approach Based on Multimodal Biometric System with Fusion of Face and Finger Vein Features
Wang, Yang
Shi, Dekai
Zhou, Weibin
SENSORS, 2022, 22 (16)
[4] Convolutional Neural Network for Finger-Vein-Based Biometric Identification
Das, Rig
Piciucco, Emanuela
Maiorana, Emanuele
Campisi, Patrizio
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2019, 14 (02) : 360 - 373
[5] Finger-vein biometric identification using convolutional neural network
Ahmad Radzi, Syafeeza
Khalil-Hani, Mohamed
Bakhteri, Rabia
TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2016, 24 (03) : 1863 - 1878
[6] Convolutional Neural Network Designs for Finger-vein-based Biometric Identification
Avci, Adem
Kocakulak, Mustafa
Acir, Nurettin
2019 11TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONICS ENGINEERING (ELECO 2019), 2019, : 580 - 584
[7] Practical Consideration in using Pre-Trained Convolutional Neural Network (CNN) for Finger Vein Biometric
Safie, Sairul Izwan
Khalid, Puteri Zarina Megat
COMMUNICATIONS ON PURE AND APPLIED ANALYSIS, 2023, 19 (02) : 163 - 175
[8] Practical Consideration in using Pre-Trained Convolutional Neural Network (CNN) for Finger Vein Biometric
Safie, Sairul Izwan
Khalid, Puteri Zarina Megat
INTERNATIONAL JOURNAL OF ONLINE AND BIOMEDICAL ENGINEERING, 2023, 19 (02) : 163 - 175
[9] Multimodal Biometric Recognition Based on Convolutional Neural Network by the Fusion of Finger-Vein and Finger Shape Using Near-Infrared (NIR) Camera Sensor
Kim, Wan
Song, Jong Min
Park, Kang Ryoung
SENSORS, 2018, 18 (07)
[10] Finger vein recognition based on PCA and fusion convolutional neural network
Al-Tamimi, Mohammed S. H.
AL-Khafaji, Ruaa S. S.
INTERNATIONAL JOURNAL OF NONLINEAR ANALYSIS AND APPLICATIONS, 2022, 13 (01): : 3667 - 3681

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