Mobile Recognition of Image Components Based on Machine Learning Methods

This paper is related to the recognition of certain components in images using machine learning methods and mobile technologies. The main result of this work is a developed system for recognizing the presence of a mask on the face using an image, which provides all the necessary information in real-time about the presence or absence of a mask on the face. When the program is turned off, statistics about the presence/absence of the mask will be recorded in the database. To achieve the goal, the following tasks were solved: the current state of the task of recognizing the presence of a mask on a person's face was analysed; existing analogs of the systems were analysed; the necessary neural network architecture was selected as one of the machine learning methods; developed a system for recognizing the presence of a mask on the face using the necessary libraries; a user graphical interface, a database model for recording statistics and additional functionality have been developed; conduct testing. Practical application has a fairly wide range, in particular, the developed intelligent system is intended for use in the subway, industrial enterprises, state institutions, educational institutions, offices, and other public places. The developed system recognizes and records statistics about the presence of a mask on a person's face using neural networks.