Intelligent-Face-Recognition-Attendance-System and Attendance_System_using_Face_Recognition
Both projects offer similar face recognition attendance systems, making them direct competitors; project A is a more comprehensive and popular choice for university settings, while project B focuses on employee attendance through a web browser.
About Intelligent-Face-Recognition-Attendance-System
turhancan97/Intelligent-Face-Recognition-Attendance-System
This project is a comprehensive face recognition-based attendance system for universities. It leverages OpenCV for face detection and recognition, Firebase for data storage, and Flask for the web interface. The system allows for student registration, face capture, and attendance tracking, providing a modern solution for attendance management.
The system employs dlib-based facial landmark detection (68-point model) for precise face alignment before matching, and implements multi-class attendance tracking where students can be enrolled across different courses with separate records. It uses Firebase Realtime Database for cloud synchronization and includes role-based access control with teacher authentication to view per-class attendance reports. The architecture separates face detection/recognition logic from the Flask web layer, supporting both webcam capture and image upload workflows for enrollment.
About Attendance_System_using_Face_Recognition
harshd23/Attendance_System_using_Face_Recognition
The purpose of this Attendance System Using Face System is to record the presence or attendance of employee through a browser by recognizing the faces captured through a webcam. For this record-keeping, a database was built to store the in-time and out-time of the employee.
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