Turkish Journal of Computer and Mathematics Education
Journal license

Journal

Turkish Journal of Computer and Mathematics Education


Volume
& Issue

Volume 14, Issue 3


Published
on


Pages

1-14


DOI

Article

Real Time Face Mask Detection System for COVID 19 Applicants


Authors

Sumaiya Samreen Affiliation:
Department of Information Technology, Malla Reddy Engineering College for Women (UGC-Autonomous), Maisammaguda, Hyderabad-500100
, Ch. Arpana Affiliation:
Department of Information Technology, Malla Reddy Engineering College for Women (A), Maisammaguda, Medchal, Telangana
, D. Spandana Affiliation:
Department of Information Technology, Malla Reddy Engineering College for Women (A), Maisammaguda, Medchal, Telangana
, D. Sheetal Affiliation:
Department of Information Technology, Malla Reddy Engineering College for Women (A), Maisammaguda, Medchal, Telangana
and D. Sandhya Affiliation:
Department of Information Technology, Malla Reddy Engineering College for Women (A), Maisammaguda, Medchal, Telangana


Abstract

COVID-19 epidemic has swiftly disrupted our day -to-day lives affecting the international trade and movements. Wearing a face mask to protect one's face has become the new normal. Soon, many public service providers will expect the clients to wear masks appropriately to partake of their services. Therefore, face mask detection has become a critical duty to aid worldwide civilization. This paper provides a simple way to achieve this objective utilising some fundamental Machine Lea rning tools as TensorFlow, Keras, OpenCV and Scikit -Learn. The suggested technique successfully recognises the face in the image or video and then determines whether it has a mask on it. As a surveillance job performer, it can also recognise a face togethe r with a mask in motion as well as in a video. The technique attains excellent accuracy. We investigate optimal parameter values for the Convolutional Neural Network model (CNN) to identify the existence of masks accurately without generating over-fitting.


Keywords

Face mask detection, deep learning CNN, machine learning


Citation

Samreen, S., Arpana, C., Spandana, D., Sheetal, D., & Sandhya, D. (2023). Real time face mask detection system for COVID 19 applicants. Turkish Journal of Computer and Mathematics Education, 14(3), 1–14.

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