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基于云端人脸识别技术的智慧课堂框架研究
引用本文:李昕昕,赵春,严张凌.基于云端人脸识别技术的智慧课堂框架研究[J].实验技术与管理,2020(6):172-175.
作者姓名:李昕昕  赵春  严张凌
作者单位:四川大学锦城学院计算机与软件学院
基金项目:教育部2017年第二批产学合作协同育人项目(201702160009);四川省科技厅重点研发项目(2019YFS0432);四川省教育厅自然科学重点课题(16ZA0422);四川大学锦城学院2017年教育科研课题特别项目(2017JCKY(特)0019)。
摘    要:论文从分析高校传统课堂存在的问题出发,提出了基于云端人脸识别技术的智慧课堂概念。通过分析智慧课堂应该具备的特征,设计了由分布式处理平台、图像处理平台、云平台和应用平台构成的智慧课堂框架。并对框架所涉及的核心技术:深度学习、人脸识别和数据挖掘进行了探讨。经仿真实验证明该框架下人脸识别模块的识别准确率达到99.43%,可以有效提高课堂考勤效率,监督教学过程,分析并管理教学效果。

关 键 词:智慧课堂  人脸识别  深度学习  数据挖掘  云平台

Research on intelligent classroom based on cloud face recognition technology
LI Xinxin,ZHAO Chun,YAN Zhangling.Research on intelligent classroom based on cloud face recognition technology[J].Experimental Technology and Management,2020(6):172-175.
Authors:LI Xinxin  ZHAO Chun  YAN Zhangling
Institution:(School of computer and software,Jincheng College of Sichuan University,Chengdu 611731,China)
Abstract:Based on the analysis of the problems existing in the university traditional classroom,this paper puts forward the concept of the intelligent classroom based on cloud face recognition technology.Through the analysis of the characteristics of the intelligent classroom,the framework of such classroom is designed,which is composed of distributed processing platform,image processing platform,cloud platform and application platform.The core technologies involved in the framework:deep learning,face recognition and data mining are also discussed.The simulation results show that the recognition accuracy of the face recognition module is 99.43%,which can effectively improve the efficiency of class attendance,supervise the teaching process,analyze and manage the teaching effect.
Keywords:intelligent classroom  face recognition  deep learning  data mining  cloud platform
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