Abstract
FACE MASK DETECTION USING CNN
*Amogh B. and Dr. Ganesh D
ABSTRACT
The COVID-19 epidemic has had a dramatic impact on our daily lives, disrupting global trade and transportation. Protecting one's face with a mask has become the new normal. Many public service providers will need clients to wear masks correctly in the near future in order to use their services. As a result, detecting face masks has become a critical responsibility in aiding worldwide society. This project shows how to achieve this goal with the help of several fundamental Machine Learning tools such as TensorFlow, Keras, OpenCV, and Scikit-Learn. The suggested approach successfully detects the face in the image and then determines whether or not it is covered by a mask. It can also detect a face and a mask in motion as a surveillance task performance. The approach achieves a level of accuracy of up to 99%. We investigate optimum parameter values using the Sequential Convolutional Neural Network model to appropriately detect the existence of masks without over-fitting.
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