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Face Mask Detection and Recognition with High Accuracy on Live Streaming Video Using Improved Yolo V4 and Comparing with Convolutional Neural Network
1st International Conference on Advanced Communication and Intelligent Systems, ICACIS 2022 ; 1749 CCIS:673-681, 2023.
Article in English | Scopus | ID: covidwho-2265380
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. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 1st International Conference on Advanced Communication and Intelligent Systems, ICACIS 2022 Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 1st International Conference on Advanced Communication and Intelligent Systems, ICACIS 2022 Year: 2023 Document Type: Article