(untitled) (JOURNAL OF SOFTWARE ENGINEERING TOOLS & TECHNOLOGY TRENDS, 2023)
Various universities are facing several issues concerning students’ fake enrollment, duplication, and authentication of student details. Here we are providing solutions to improve student enrollment process for various exams by using convolutional neural networks (CNN) and OpenCV (Open-Source Computer Vision Library). A solution to the existing system must be versatile and precise. If the project aims to be used for large-scale deployments, then it must be adaptable and accurate in order to be successful. We have used advanced technologies and algorithms such as Convolutional Neural Networks (CNN) and OpenCV for accurate face detection and recognition, as well as the MERN stack for verifying student details. Our implementation fulfills the problem statement by solving the primary concern of universities regarding authentication, duplication, and fake enrollment of the students. After successful verification, the student will be directed to the exam page where any educational activities related to exam can be performed.