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ai/ml
2021
AI Face Recognition Attendance
University FYP achieving 97.5% accuracy at 25 FPS for automated classroom attendance.
Key Metrics
97.5%
Accuracy
25
FPS
150+
Students
About This Project
My final year project at University of Central Punjab - an AI-powered face recognition attendance system. The system achieved 97.5% accuracy at 25 FPS, processing 150+ students efficiently.
Built with FaceNet for face embeddings, MTCNN for face detection, OpenCV for video processing, PostgreSQL for data storage, and PyQt5 for the desktop interface.
Technologies Used
FaceNet MTCNN OpenCV PostgreSQL PyQt5 Python
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