Exploring Deep Learning Methods for Face Mask Detection


Authors : MARITTA STEPHEN; USHA K

Volume/Issue : Volume 8 - 2023, Issue 1 - January

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3WAQ2p7

DOI : https://doi.org/10.5281/zenodo.7564241

The global epidemic COVID-19 has brought about a drastic change in the lives of mankind. Health and economic systems were severely impacted by the global epidemic. The world was under strict restrictions to fight and control the pandemic. Wearing a face mask is an essential protective measure to prevent the dissemination of virus in public. The reports suggests that a large population often ignore or tend to avoid wearing masks amid strict rules. The project's objective is to devise a face mask detector that can determine from visual inputs if an individual is wearing a mask. This work also focuses on face mask detection of a moving face and can perform real time face mask detection. Tensor Flow, Keras, OpenCV and Scikit-Learn were used to buld the detector along with Mobilenetv2 for face mask classification SSD (Single Shot Multibox detector) with Resnet as the base for face detection.

Keywords : Deep Learning, Object Detection, Face Recognition, TensorFlow, Keras, OpenCV, SSD, Mobilenet

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