Implementation of Deep Learning in the Application of Lecture Attendance System with Face Recognition Technology Based on OpenCV

Abstract


 
 
 OpenCV, as an object detection library, is employed as the foundation in the development of a facial recognition system. This system utilizes the Haar Cascade Classifier method embedded in OpenCV for facial detection, providing an efficient approach to identifying individuals. The research is conducted using the Python programming language. The initial stages involve a literature review, followed by data collection necessary for system training. System design incorporates the implementation of the Haar Cascade Classifier method from OpenCV, along with data analysis to comprehend and optimize facial recognition outcomes. After progressing through these stages, the system is tested to evaluate facial features that can reliably identify individuals. The experimental results are expected to offer valuable insights into the development of facial recognition technology using OpenCV, with potential applications across various domains.