基于人脸识别的高校学生考勤管理系统

Attendance management system of school based on face recognition

面对信息化时代考勤管理,尤其是以非接触式高校考勤为代表的具有多样化、个性化考勤场景,结合前沿的深度学习方法来提取人脸特征,设计完成了基于人脸识别的高校考勤管理系统。该人脸识别的高校考勤管理系统采用卷积神经网络训练图像数据,提取特定维度的人脸特征。然后采用Softmax分类器分类,以达到人脸识别的目的。整体采用C/S架构,结合PyQt5进行数据展示和管理员控制,实现了功能多样,核心突出的考勤管理系统。该系统以考勤管理为核心,对考勤数据进行二次整理,实现了数据可视化、考勤监督、打卡提醒等特色功能。经测试运行,系统具有运行稳定、操作简单以及对环境要求低的优点,基本满足高校人脸考勤的需求。

Faced with the attendance management in the information age,especially with the non-contact college attendance as the representative,the diversified and personalized attendance scene,combined with the cutting-edge deep learning method in the text,the facial features is extracted,and based on face recognition the attendance management system is designed.The convolution neutral network(CNN)training image data is used to extract face features of specific dimensions,and then softmax classifier classification is used to achieve the purpose of face recognition.The overall adoption of C/S architecture,combined with PyQt5 for data display and administrator control,to achieve a variety of functions,core outstanding attendance management system.The system takes attendance management as the core,and secondary finishing of attendance data is carried to realize data visualization,attendance supervision,punch card reminder and other special functions.After testing and running,the system has the advantages of stable operation,simple operation and low environmental requirements,which basically meets the needs of college face attendance..