High response speed and accuracy real-time mask-detection system for chinese campuses

Abstract

Due to the increasing number of students studying in universities globally, the need for effective and timely safety measures has become more critical. This study aims to provide a high tech monitoring system that can help universities realize the security they need. The main functions are mask detection. Among them, mask detection is mainly used to determine if students are wearing the right masks. This paper also carried out algorithm provinciation for two kinds of detection.In the mask detection function, YOLOV4-Tiny model is used, and SPP is added and improved on this basis. And replace the feature enhancement network with the path aggregation network (PAN). After the experiment, the accuracy was improved, Precision (P) and Recall (R) increase by 1.61% and 4.14%.and the response speed of mask detection was improved(The FPS reached 98.67) too. It greatly improves the efficiency of the system and provides security for students.