Detection of Face Mask using Convolutional Neural Network (CNN) based Real-Time Object Detection Algorithm You Only Look Once-V3 (YOLO-V3) Compared with Single-Stage Detector (SSD) Algorithm to Improve Precision

Proposed work refers to detect face masks using a CNN based on a real-time object detection algorithm in comparison to (Single Stage Detector) SSD, Yolo-V3. The Yolo-V3 algorithm is proposed and compared to the SSD algorithm. The sample size was calculated using G power (80%), and it was discovered to be 40. (i.e. For each group 20). There is a statistically significant difference of 0.000637 (p<0.5) between the two groups. The Yolo-V3 has an average accuracy of 91.28 and the SSD has an average precision value of 86.65. The Yolo-V3 algorithm has improved for preventing the spread of COVID-19 through precautionary measures.