Driver Fatigue Detection Through Chaotic Entropy Analysis of Cortical Sources Obtained From Scalp EEG Signals-Reference-Cited by-同舟云学术

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Driver Fatigue Detection Through Chaotic Entropy Analysis of Cortical Sources Obtained From Scalp EEG Signals

Published:2020-01 Issue:1 Volume:21 Page:185-198
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Chaudhuri Aritra^ORCID,Routray Aurobinda^ORCID

Funder

Ministry of Human Resources and Development, Government of India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/8946909/08626762.pdf?arnumber=8626762

Cited by 52 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. Addressing Imbalanced EEG Data for Improved Microsleep Detection: An ADASYN, FFT and LDA-Based Approach;Diyala Journal of Engineering Sciences;2024-09-01

2. Efficient detection of driver fatigue state based on all-weather illumination scenarios;Scientific Reports;2024-07-24

3. Enhancing Road Safety Through Cost-Effective, Real-Time Monitoring of Driver Awareness with Resource-Constrained IoT Devices;2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC);2024-07-02

4. TFAC-Net: A Temporal-Frequential Attentional Convolutional Network for Driver Drowsiness Recognition With Single-Channel EEG;IEEE Transactions on Intelligent Transportation Systems;2024-07

5. A Survey of EEG-Based Driver State and Behavior Detection for Intelligent Vehicles;IEEE Transactions on Biometrics, Behavior, and Identity Science;2024-07

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