Lightweight mask wearing detection algorithm in aliasing scenario
A lightweight mask wearing detection algorithm is proposed to address the low recognition rate of mask wearing de-tection in mixed scenes and the difficulty of deploying existing detection models with complex structures.Firstly,the lightweight network MobileNetv3 serves as a feature extraction network for aliasing scene images;Secondly,channel mixing is proposed,which utilizes convolutional kernels from different receptive fields in space for feature extraction and enhances feature information;Finally,a loss function was designed to solve the problem of imbalanced data classes and improve the accuracy of model detection.In public dataset testing,the average detection accuracy of the model is 78.1%,and the FPS reaches 65.53 Hz,meeting the require-ments for deployment on small devices.
NETL
NSTL
万方数据
维普
