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With the advancement of technology and due to the recent pandemic situation, the education sector has turned to the online teaching method. But the main problem here is the inconvenience and irregularities in the student's attendance. To ensure traditional attendance and reduce time wastage, this research aims to explore and implement an automated attendance marking system using facial recognition technology. This will enable students to be marked present or absent in real-time and will also help teachers to identify students who are present or absent for the online session. As a novelty of this research gives a more efficient and accurate method for attendance marking and eliminating manual and false attendance marking in online sessions. The proposed system employs the latest advancements in image processing and machine learning techniques such as the Haar Cascade feature and LBPH algorithm to accurately detect and recognize the face of a student. The performance of the system is evaluated on its own dataset which was the images of students captured through a video stream from a web camera and the results demonstrate through a confusion matrix its effectiveness in accurately recognizing faces and marking attendance in real-time. The results showed that the attendance system achieved 99.22% accuracy and can accurately mark the attendance of students in an Excel sheet. This real-time GUI-based system is unique in that it revolutionizes the traditional attendance marking process by automating it and providing real-time attendance data.
Fernando et al. (Sat,) studied this question.