摘要
在评价学生的学习状态和课堂教学质量的依据中,学生在课堂上的姿态和表现尤为重要。通过人工进行记录的传统课堂监测时间较长、速度较慢并且监测工作量较大,易于导致监测数据不客观准确、不全面的问题产生。改进的YOLOv4算法具有较快的处理速度和较高的准确性,对于某些学生姿态的检测具有更好的效果。
In the basis of evaluating students'learning status and classroom teaching quality,students'posture and performance in the classroom are particularly important.The traditional classroom monitoring by manual recording takes a long time,the speed is slow and the monitoring workload is large,which can easily lead to the problems that the monitoring data are not objective,accurate and not comprehensive.The improved YOLOv4 algorithm has faster processing speed and higher accuracy,and has a better effect for the posture detection of some students.
出处
《科技创新与应用》
2022年第18期51-54,共4页
Technology Innovation and Application
基金
黑龙江省大学生创新创业训练计划项目(s202110214028)。
