AI-Powered Attendance Management System Using Facial Recognition
Abstract
Traditional ways of keeping track of attendance, including signing in by hand or swiping an ID card, can take a long time, be wrong, and be open to proxy attendance. This project presents an Attendance Management System Using Facial Recognition to solve these problems. This system is faster, more accurate, and safer than the current ones. The system uses cutting-edge facial recognition technology to automatically find and recognize student faces in real time. The system uses a pre-trained deep learning model and a high-resolution camera to take pictures, identify people, and mark attendance without any help from a person. Face detection and identification algorithms make sure that the results are quite accurate, even when the lighting or face expressions change. The program has a simple UI and capabilities like automatic attendance tracking, reporting, and data storage. It also makes attendance reports in real time, which cuts down on the work of administrators and makes everything run more smoothly. This approach makes attendance monitoring more reliable while lowering the chance of fake entries. Possible future improvements include support for larger datasets through continuous model training, integration with mobile devices, and cloud-based data storage. The study shows how AI and computer vision may make common administrative jobs easier for schools and businesses.
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