AI And Imaged Processing Based Student’s Attendance System

Abstract Tracking attendance is a crucial function for educational institutions and organizations. To simplify this process, we propose an AI-based solution. This system can recognize known students, update records of attendance and show information of the student on screen. It also sends information to Firebase that stores both student and image data, thus it can be easily obtained. The code is user friendly and displays attendance with student detail and also marks attendance by face recognition which prevents false attendance. The system consists of a database of facial images of students of a particular class. So, for accurate attendance tracking, we use Convolutional neural networks(CNNs) via transfer learning. Overall, this code serves as an innovative solution for automating attendance tracking in educational institutions, reducing manual work, and increasing accuracy through AI-driven face recognition technology. Keywords – Automated Attendance tracking, user- friendly, Convolutional Neural Networks (CNNs), transfer learning, face recognition