YOLO-LHD: an enhanced lightweight approach for helmet wearing detection in industrial environments
Lianhua Hu,
Jiaqi Ren
Abstract:Establishing a lightweight yet high-precision object detection algorithm is paramount for accurately assessing workers’ helmet-wearing status in intricate industrial settings. Helmet detection is inherently challenging due to factors like the diminutive target size, intricate backgrounds, and the need to strike a balance between model compactness and detection accuracy. In this paper, we propose YOLO-LHD (You Only Look Once-Lightweight Helmet Detection), an efficient framework built upon the YOLOv8 object dete… Show more
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