A Convolutional Neural Network Model and Software Tool for Classifying the Presence of a Medical Mask on a Human Face

Abstract

A model of a convolutional neural network, a database for training a neural network, and a software tool for classifying the presence of a medical mask on a person’s face, which allows recognizing the presence of a medical mask from the transmitted image, have been developed. The structure of the neural network model was optimized to improve classification results. In addition, the development of the user interface was carried out. The developed application was tested on a set of random images. The resulting model demonstrated high accuracy and robustness in solving the task of classifying the presence of a medical mask on a person’s face, which allows automating measures to protect people from the spread of diseases. The implemented application meets the requirements for speed and quality of classification. Further improvement of the classification quality of CNN can be done by collecting a larger dataset and researching other CNN architectures.