Abstract
With the influence of novel coronavirus, wearing masks is becoming more and more important. If computer vision system is used in public places to detect whether a pedestrian is wearing a mask, it will improve the efficiency of social operation. Therefore, a new mask recognition algorithm based on improved yolov3 is proposed. Firstly, the dataset is acquired through network video; secondly, the dataset is preprocessed; finally, a new network model is proposed and the activation function of YOLOv3 is changed. The average accuracy of the improved YOLOv3 algorithm is 83.79%. This method is 1.18% higher than the original YOLOv3.
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Meng, F., Wei, W., Cai, Z., Liu, C. (2021). Application of Improved YOLOv3 Algorithm in Mask Recognition. In: Nguyen, N.T., Chittayasothorn, S., Niyato, D., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2021. Lecture Notes in Computer Science(), vol 12672. Springer, Cham. https://doi.org/10.1007/978-3-030-73280-6_43
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