Research on Driver Facial Fatigue Detection Based on Yolov8 Model
<|reference_start|>Research on Driver Facial Fatigue Detection Based on Yolov8 Model: In a society where traffic accidents frequently occur, fatigue driving has emerged as a grave issue. Fatigue driving detection technology, especially those based on the YOLOv8 deep learning model, has seen extensive research and application as an effective preventive measure. This paper discusses in depth the methods and technologies utilized in the YOLOv8 model to detect driver fatigue, elaborates on the current research status both domestically and internationally, and systematically introduces the processing methods and algorithm principles for various datasets. This study aims to provide a robust technical solution for preventing and detecting fatigue driving, thereby contributing significantly to reducing traffic accidents and safeguarding lives.<|reference_end|>
@article{zhou2024research,
    title={Research on Driver Facial Fatigue Detection Based on Yolov8 Model},
    author={Chang Zhou, Yang Zhao, Shaobo Liu, Yi Zhao, Xingchen Li, Chiyu Cheng},
    journal={arXiv preprint arXiv:2406.18575},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.18575},
    primaryClass={cs.CV cs.LG}
}