Attention-based Deep Learning Model Using Adaptive Margin Loss For Finger-Vein Recognition-Reference-Cited by-同舟云学术

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Attention-based Deep Learning Model Using Adaptive Margin Loss For Finger-Vein Recognition

Published:2023-04-14 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 3rd International Conference on Electronic Communications, Internet of Things and Big Data (ICEIB)
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Author:

Ke Liang-Ying¹,Yeh Shu-Yen²,Hsia Chih-Hsien¹

Affiliation:

1. National Llan University,Department of Computer Science and Information Engineering,Yilan,Taiwan

2. Taipei European School,Taipei,Taiwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10169134/10169905/10170355.pdf?arnumber=10170355

Reference14 articles.

1. New Hierarchical Finger-Vein Feature Extraction Method for iVehicles

2. Semi-Supervised Learning with Attention-Based CNN for Classification of Coffee Beans Defect

3. YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors

4. MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation

5. MMRAN: A novel model for finger vein recognition based on a residual attention mechanism

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Robust Finger Vein Recognition Based on Lightweight Attention Convolutional Neural Networks;2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC);2023-10-31

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