基于卷积神经网络的人脸识别研究与设计

Research and Design of Face Recognition Based on Convolutional Neural Network

人脸识别在社会管理方面起着越来越重要的作用。通过卷积网络神经系统的自适应学习,可以使用人工智能技术达到准确识别人脸的目的。传统的人工签到、指纹识别在身份认证应用中暴露出越来越多的缺陷,因此市场急需一种精确的身份认证方式的出现。文中从卷积神经网络在人脸识别上的应用入手,借助face++公司提供的运行平台,分析并设计了可完成较高准确率人脸识别的神经网络算法。

Face recognition plays an increasingly important role in social management. Through adaptive learning of convolution network nervous system,artificial intelligence technology can be used to accurately recognize human faces. Traditional manual check-in and fingerprint identification have exposed more and more defects in the application of identity authentication,so the market urgently needs an accurate way of identity authentication. Starting with the application of convolutional neural network in face recognition,this paper analyses and designs a neural network algorithm which can achieve high accuracy of face recognition with the help of the operation platform provided by face++ company.