Design and Implementation of Classroom Student Behavior Image Analysis System Based on Computer Vision
This article designs and implements a classroom student behavior image analysis system based on computer vision.The system adopts the latest object detection algorithm YOLOv5s,collects classroom images through intelligent cameras,detects student behavior in real time and analyzes it to improve classroom teaching effectiveness and student learning quality.This article collects numerous student behavior image materials,and after data preprocessing and enhancement,establishes a database suitable for YOLOv5s.Afterwards,a classroom student behavior detection model based on YOLOv5s was trained using the collected classroom student behavior dataset,which can quickly and accurately identify various behaviors of students in the classroom,such as raising hands,listening,reading,etc..
万方数据
维普
