Improving Accuracy in Face Mask Detection based on Tensorflow Compared with Viola-jones Method for Pandemic Control

Abstract

Aim:This project aims to Improve Accuracy in Face Mask detection based on TensorFlow compared with Viola-Jones method for Pandemic Control .Materials and Methods: Tensorflow method and Viola-Jones method are chosen as two groups and each group with 15 samples respectively, which are collected using the training image datasets. G Power =0.8. Result: The independent sample t-test result shows that the Accuracy in (%) is improved for Artificial Intelligence-based TensorFlow with a mean (98.82) when compared with the Viola-Jones method (89.61) with a significance (p = 0.007). Conclusion: The results show that the accuracy in TensorFlow-based Facemask detection is significantly better compared to the Viola-Jones method.