DeepVision Attendance: A Visual Recognition System for Automated Attendance Tracking

It might take a while for teachers or administrators to manually mark each student’s attendance in numerous regular classes. By creating a visual attendance record utilizing facial recognition technology, this paper hopes to solve this problem. A collection of photos including the faces of people present in a certain class will be used by the system. The model will provide distinctive identification marks or patterns for each pupil by analyzing these photographs. When the camera is started using the created model, the system will instantly detect people and note their attendance. To achieve precise and trustworthy recognition of each individual, the technique uses the hog (histogram of oriented gradients) and Convolutional Neural Network methods. The project makes use of the OpenCV library’s capabilities to accomplish this, which offers a number of face recognition-related tools and features. This technique makes taking attendance easier and more time-efficient for both the teaching staff and the students.