A Novel Learning Model of Driver Fatigue Features Representation for Steering Wheel Angle-Reference-Cited by-同舟云学术

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A Novel Learning Model of Driver Fatigue Features Representation for Steering Wheel Angle

Published:2022-01 Issue:1 Volume:71 Page:269-281
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Li Zuojin^ORCID,Chen Liukui,Nie Ling,Yang Simon X.^ORCID

Funder

National Natural Science Foundation of China

Natural Science Foundation of Chongqing

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/25/9687310/09625807.pdf?arnumber=9625807

Cited by 49 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. Proposal of a Cost-Effective and Adaptive Customized Driver Inattention Detection Model Using Time Series Analysis and Computer Vision;World Electric Vehicle Journal;2024-09-03

2. EEG-Based Driver Fatigue Detection Using Spatio-Temporal Fusion Network With Brain Region Partitioning Strategy;IEEE Transactions on Intelligent Transportation Systems;2024-08

3. Self-Supervised Multi-Granularity Graph Attention Network for Vision-Based Driver Fatigue Detection;IEEE Transactions on Emerging Topics in Computational Intelligence;2024-08

4. Evaluating the Role of AI and Empirical Models for Predicting Regional Economic Growth and Transportation Dynamics: An Application of Advanced AI Approaches;International Journal of Transportation Science and Technology;2024-08

5. Human–Machine Shared Control for Path Following Considering Driver Fatigue Characteristics;IEEE Transactions on Intelligent Transportation Systems;2024-07

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