Published Paper Details:

Abstract -- Many different fields, such as autonomous attendance devices based on face recognition, employee attendance records, safety, protection, and police applications like identifying thieves in photos that aid in their capture, can benefit from the gathering of images from cameras or closed-circuit television cameras and the application of recognition outcomes based on facial detection and recognition. With face detection and recognition technology, we can reduce human labour and improve security when it comes to recording student attendance for lectures, labs, or sections. This system allows the lecturer or faculty member to make options about who to record the attendance of each student. It saves a great deal of time and work, particularly in large class lectures. Exam-related concerns can be resolved with the use of this pupil's history, which is utilised in the monitoring system to demonstrate the application of facial detection tools. The suggested system uses the Haar cascade technique for facial feature identification and segmentation. It is a CNN-based facial identification method. Comparing the proposed method to state-of-the-art methods, it reached precision of 98%.