From a comprehensive review of facial mask detection techniques, there are several algorithms based on deep learning, namely You Only Look Once (YOLO), Single Shot Detector (SSD), RetinaFace, and (Faster Recurrent Convolutional Neural Network) Faster R-CNN. Previous studies focused on the detection accuracy of face masks using a two-stage detection model (ie, Faster R-CNN), while single-stage detectors (ie, YOLO) achieved fast inference times but lower accuracy. The training results in this study show that the Precision value is consistent at 0.4 – 0.8. While the maximum recall value is 0.6. Future research will focus on using YOLOv7 for other object detection.
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