Currently, most fatigue driving detection methods rely on complex neural networks whose feasibility in hardware implementation needs to be further improved. This paper proposes an embedded device-oriented fatigue driving detection method based on a lightweight YOLOv5s. Firstly, a YOLOv5s face detection network with a parametric-free attention mechanism is designed to enhance the focus on face regions during face detection. Then, a practical facial landmark detector model is improved by integrating multi-scale feature fusion with Ghost module, which can adapt to the variations brought by differ...
