Research on intelligent classroom attendance management based on feature recognition

Abstract

The regular attendance method is affected by many factors in the classroom intelligent attendance, which leads to lower attendance efficiency. In order to improve the efficiency of intelligent classroom attendance management, this study uses face recognition technology as a technology to study the attendance mode of face feature recognition. In the study, we used the multi-task cascade convolutional neural network to identify the face features and used the MTCNN face detection algorithm frame by frame for the sampled frame images and normalized the single face region image cropping to the face recognition model input size. Thereafter, the normalized single face region image is taken for feature extraction. In addition, this paper analyzes the effectiveness of the algorithm by design comparison experiments. The research shows that the algorithm proposed in this study has certain practical effects and can provide theoretical reference for subsequent related research.