ABSTRACT
This paper delineates the algorithms to decipher the persons who are wearing mask. Sensing faces with sealings is a thought-provoking task due to the nonappearance of huge datasets of masked faces, thereby we have gathered a colossal of datasets from various resources and arranged them in a structured form. Preprocessing methods were applied on the dataset for reducing time and space complexity of an algorithm. The minimized dataset is used for training, utilizing this dataset we have developed different models using Convolution Neural Networks (CNN). The results have been comprehended from this model and an impeccable result of 91% accuracy is obtained using convolution neural networks. The construction of Covid-19 face mask detector here today can possibly be used to help ensure your safety and the security of others. This detection system can also be widely used in travel scenes, with mobile phone and surveillance images. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.