Face Fatigue Feature Detection Based on Improved D-S Model in Complex Scenes
Author:
Affiliation:
1. College of Electrical Engineering, Chongqing University of Science and Technology, Chongqing, China
2. Shanghai Ecar Technology Company Ltd., Jiading, China
Funder
Chongqing Natural Science Foundation Project
Industry-University-Research Innovation Fund of the Ministry of Education of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10247545.pdf?arnumber=10247545
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1. Design of Real-time Drowsiness Detection System using Dlib
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3. A multi-modal information fusion-based method for detecting fatigue driving of train drivers;li;Journal of Railway,2022
4. Three Triangle Method for Face Recognition using Dlib and OpenCV
5. SENE: A novel manifold learning approach for distracted driving analysis with spatio-temporal and driver praxeological features
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