An innovative classroom real-time facial recognition system based on YOLOv8 algorithm to enhance teaching efficiency

This paper introduces an innovative classroom teaching platform that utilizes the YOLOv8 algorithm and real-time video surveillance technology to recognize and analyze the facial expressions of students and teachers. By analyzing the attention and emotional states of students during class, the system generates real-time feedback to help teachers adjust their teaching strategies, thereby improving classroom teaching efficiency. The practical application of the platform demonstrates its significant effectiveness in enhancing students' attention, classroom participation, and knowledge mastery. Additionally, the paper proposes further optimizations to the algorithm, hardware upgrades, and application expansion to enhance the platform's functionality and applicability.