Deep Learning-Based Fatigue Detection for Online Learners-Reference-Cited by-同舟云学术

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Deep Learning-Based Fatigue Detection for Online Learners

Published:2022-08-19 Issue: Volume: Page:
ISSN:
Container-title:2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI)
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Author:

Chen Yaxi¹,Zhao Dinghao¹,He Guixian¹

Affiliation:

1. Southwest Minzu University,Department of Computer Science and Engineering,Chengdu,China

Funder

Ministry of Education

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9904023/9904007/09904096.pdf?arnumber=9904096

Reference15 articles.

1. Research on driving fatigue detection method based on ECG;qun;PhD observation,2008

2. Yawn analysis with mouth occlusion detection

3. Fusion algorithm of face detection and head pose estimation based on SSD model;yang;Journal of Jiangsu University,2019

4. Research on efficient training algorithm of deep learning model;kai;PhD observation,2016

Cited by 2 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. Real Time Detection of Learner Fatigue in E-Learning Environments through the Combination of Eye and Mouth Features;2024 11th International and the 17th National Conference on E-Learning and E-Teaching (ICeLeT);2024-02-27

2. Drowsiness Sensing System of Driver Based on Behavioral Characteristics to Prevent Road Accidents Using RealTime Optimized Computer Vision;2;2023-06-01

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