Mask wearing detection method based on SSD-Mask algorithm

With the spread of COVID-19 all over the world, under the background of normalized epidemic prevention and control, proper wearing and using of masks can effectively filter virus pathogen particles. In order to reduce the infection rate of ordinary people and improve the efficiency of monitoring people wearing masks in public places, this paper improves a method of face mask wearing detection in natural scenes. On the basis of SSD algorithm, SSD-Mask introduces a channel attention mechanism to improve the ability of the model to express salient features. At the same time, the information of different feature levels is fully utilized, and the loss function is optimized. The final experimental results show that the algorithm can effectively achieve the goal of face recognition and mask detection.