Facial Recognition-Based Classroom Attendance System Utilizing Deep Learning

In recent years, artificial intelligence technologies, especially facial recognition, have made significant strides. With its high precision and efficiency, facial recognition has shown great potential and advantages in areas such as identity verification and behavior analysis. Classroom learning is the main channel through which students acquire knowledge, develop skills, and improve their competencies. A well-organized classroom attendance system is essential for ensuring the effective implementation and smooth execution of teaching plans. This system is based on an OpenCV and PyQt5 facial recognition client, utilizing the LBPH algorithm to achieve efficient facial recognition. In addition to providing a simple check-in function, the system offers a complete registration process and data management features. In practical use, students simply need to check in by facing the camera, allowing the system to automatically recognize the student's face and record the attendance data. This significantly simplifies the check-in process for both teachers and students, thereby improving classroom management efficiency.