The student attendance control system based on face recognition

Currently, one of the significant factors for improving the quality of training of specialists is the control of student attendance. This process can be automated. The paper suggests an approach to building a studentattendance control system based on face recognition technology, which allows you to identify many people at thesame time without direct contact with them and without using expensive equipment. This approach is based onthe convolutional neural networks RetinaFace and ResNet, selected based on the review of modern methods offacial recognition presented in the paper. The architecture of our attendance control system is complemented byimage preprocessing procedures, which, according to our proposed method based on the BREN measure, checkthe image quality and, if necessary, apply algorithms to the image to reduce noise, sharpen, increase brightnessand align colors. The results of computational experiments are presented, which have shown a higher efficiency ofthe proposed approach compared with analogues.