Face Mask Detection using Vision Transformer

Technological advancement has provided many facilities and made life easy but every coin has two sides. As the life of humans has become comfortable but at the same time many new problems are arising. In recent years humans are fighting fatal diseases like covid-19. The pandemic has changed life drastically and as an ill effect of it, social distancing and masks have become a societal norm. The proposed research focuses on the use of Artificial Intelligence and Image Processing to fight such deadly viruses and Deep Learning can be used to stop the spread of the virus by enforcing the use of face-mask. Vision Transformers are used to identify whether the human face is with a mask or without a mask. The study of vision transformers is carried out for a dataset of less than a thousand images and vision transformers are found to have an accuracy equal to 0.86. Comparative analysis of the vision transformer with different image patch sizes is also carried out and inferred that an increase in the patch size of images reduces the accuracy of the vision transformer. This paper focuses on vision transformers being a novel method for face mask recognition.