Safety helmet wearing detection algorithm based on lightweight FastestDet
Haibo Jin, Fei Yuan · 2023
Abstract—Aiming at the problems of long reasoning time and high hardware requirements of workers ' helmet wearing detection model in existing construction sites, a lightweight helmet wearing detection algorithm based on improved FastestDet is proposed. Firstly, the FASTDET backbone network is optimized to further reduce the number of parameters while ensuring accuracy. Secondly, the spatial pyramid pooling module is changed from SPP to SimSPPF proposed by Meituan YOLOv6, which accelerates the recognition speed. Finally, the EMA attention mechanism is introduced at different locations to enhance the perception ability of the model. The experimental results show that the recall rate and mAP of the improved FastestDet algorithm are 1.3 % and 1.7 % higher than FastestDet, respectively. And the inference speed is faster than other models.