基于大数据的卷积神经网络技术在课堂人脸识别应用  

Application of convolutional neural network based on big data in classroom face recognition

作　　者：汤双霞[1] TANG Shuangxia(Guangzhou Panyu Vocational and Technical College,Guangzhou 511483,China)

机构地区：[1]广州番禺职业技术学院,广州511483

出　　处：《智能计算机与应用》2019年第2期255-256,259,共3页Intelligent Computer and Applications

基　　金：项目课题(2017GGXJK051)的研究成果之一

摘　　要：近年来,人脸识别已经成为研究热点。本文即针对卷积神经网络和传统人脸识别技术的应用及进展给出研究论述。接下来,运用人脸识别技术,就能够在课堂教学过程中的无干扰状态下,采集学生的实时人脸图像,并利用统计学原理进行精准的人脸识别,可完成学生个体的专注度分析。有利于本校的教育教学改革,提高办学水平;有利于教育行业技术进步,提高行业科技含量。In recent years,face recognition has become a research hotspot. This paper gives a research and discussion on the application and progress of convolutional neural networks and traditional face recognition technology. Face recognition technology can collect real-time face images of students in the process of classroom teaching without interference. The paper uses statistical principles to realize the correct face recognition and complete the analysis of students’ classroom concentration. It is conducive to the reform of education and teaching in the author’s school,for the improvement of the level of running a school,to the technological progress of the education industry,for the improvement of the technological content of the industry.

关 键 词：卷积神经网络 人脸识别 课堂 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]