A high compatibility finger vein image quality assessment system based on deep learning-Reference-Cited by-同舟云学术

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A high compatibility finger vein image quality assessment system based on deep learning

Published:2022-06 Issue: Volume:196 Page:116603
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Ren Hengyi,Sun Lijuan,Guo Jian,Han Chong,Cao Ying

Funder

National Natural Science Foundation of China

Anhui Science and Technology Department

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference47 articles.

1. Recognition of COVID-19 disease from X-ray images by hybrid model consisting of 2D curvelet transform, chaotic salp swarm algorithm and deep learning technique;Altan;Chaos, Solitons & Fractals,2020

2. Digital currency forecasting with chaotic meta-heuristic bio-inspired signal processing techniques;Altan;Chaos, Solitons & Fractals,2019

3. A new hybrid model for wind speed forecasting combining long short-term memory neural network, decomposition methods and grey wolf optimizer;Altan;Applied Soft Computing,2021

4. Fusion of band limited phase only correlation and width centroid contour distance for finger based biometrics;Asaari;Expert Systems with Applications,2014

5. A finger vein image-based personal identification system with self-adaptive illuminance control;Chen;IEEE Transactions On Instrumentation And Measurement,2017

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1. CoSTA: Co-training spatial–temporal attention for blind video quality assessment;Expert Systems with Applications;2024-12

2. A sequential combination of convolution neural network and machine learning for finger vein recognition system;Signal, Image and Video Processing;2024-08-14

3. Design and Implementation of a Self-Supervised Algorithm for Vein Structural Patterns Analysis Using Advanced Unsupervised Techniques;Machine Learning and Knowledge Extraction;2024-05-31

4. Reverse Attention-Based Multi-Feature Interaction Network for Finger Vein Image Quality Evaluation;IEEE Signal Processing Letters;2024

5. Fed-UIQA: Federated Learning for Unsupervised Finger Vein Image Quality Assessment;Lecture Notes in Computer Science;2024

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