多注意力机制的口罩检测网络

Multi-Attention Mechanism of Mask Wearing Detection Network

提出一种口罩佩戴检测模型,引入多注意力机制,提升了网络特征挖掘能力;利用柔性非极大抑制方法,消除多余目标检测框.在公共数据库上的仿真实验表明,该模型检测人脸口罩佩戴的平均精度达到93.81%,帧率达到11.8 fps,能有效地进行人脸口罩佩戴检测.

A mask in public places can effectively control the transmission of the coronavirus.To this end,a mask wearing detection model is proposed.The model introduces a multi-attention mechanism to improve the network feature mining ability and uses soft-NMS methods to eliminate redundant target detection boxes.A simulation experiment is conducted on a public database.The average accuracy of the proposed face mask wearing detection reaches 93.81%,and the frame rate reaches 11.8 fps.The experimental results show that the model can effectively detect the face mask wearing.