Abstract
The aim of this research is to detect face masks using Convolutional Neural network (CNN) algorithm and comparing it with the Yolo v4 algorithm. The study includes two groups namely, CNN algorithm and yolo v4 algorithm. The total sample size is 40 with pretest power of 0.8. In order to evaluate how well CNN algorithm methods perform, accuracy values are calculated. Using SPSS software, CNN algorithm method was found to be 92.65% accurate while improved Yolo v4 was found to be 85.87% accurate. 0.000 p(2-tailed) is obtained for the model. Using CNN, it was proved significant improvements to performance than improved Yolo v4.
C. M. Kandan—Research Scholar.
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Kandan, C.M., Vidhya, K. (2023). Face Mask Detection and Recognition with High Accuracy on Live Streaming Video Using Improved Yolo V4 and Comparing with Convolutional Neural Network. In: Shaw, R.N., Paprzycki, M., Ghosh, A. (eds) Advanced Communication and Intelligent Systems. ICACIS 2022. Communications in Computer and Information Science, vol 1749. Springer, Cham. https://doi.org/10.1007/978-3-031-25088-0_59
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