摘要
提出了一种基于机器视觉和深度学习的智能无人零售系统。采用嵌入式的ARM9和各种传感器模块组成前端采集系统,在服务器上用训练好的卷积神经网络模型分别对物品进行动态和静态检测识别,然后将识别信息反馈给数据库,由数据库整理所有信息,最终确定顾客订单信息。本系统使用前端硬件在无人售货柜上进行图像采集并在服务器的Caffe框架上进行测试,结果表明该系统的实时准确率达到99%。
This paper proposes an intelligent automated vending system based on machine vision and deep learning.The embedded ARM9 and various sensors are used to form the front-end acquisition system.The trained convolutional neural network is used to detect and identify the goods dynamically and statically on the server.Then the identifying information will be fed back to the databases,and the databases will integrate all the information.Finally it will determine the order information of customers.This system uses front-end hardware to acquire images on the automated vending counter and test them on the server's Caffe framework,and the result shows that the accuracy of this system can reach 99%in real time.
作者
林付春
张荣芬
何倩倩
刘宇红
Lin Fuchun;Zhang Rongfen;He Qianqian;Liu Yuhong(College of Big Data and Information Engineering,Guizhou University,Guiyang 550025,China)
出处
《电子技术应用》
2018年第9期96-98,103,共4页
Application of Electronic Technique
基金
贵州省科技计划项目(黔科合平台人才[2016]5707)
