计算机应用与软件2017，Vol.34Issue(11)：109-112,118,5.DOI:10.3969/j.issn.1000-386x.2017.11.020
基于卷积神经网络的物品识别系统设计与实现
DESIGN AND IMPLEMENTATION OF OBJECT RECOGNITION SYSTEM BASED ON CONVOLUTIONAL NEURAL NETWORK
严圣军 1吴谨1
作者信息
- 1. 武汉科技大学信息科学与工程学院 湖北武汉430081
- 折叠
摘要
Abstract
In order to obtain the information of the unknown goods quickly,the separation of server and client architecture is adopt to design and implement a object recognition system on the computer side and Android mobile terminal based on convolution neural network.Firstly,it pre-processed the local pictures or cell phone photos uploaded from the client side,and then built a convolutional neural network by using the pre training model to extract image features and classified them.Finally,it returned the result to the client via a network connection to complete the object recognition.The experimental results show that the system has good online recognition ability,and this will greatly improves the way people access to information,it is more convenient and efficient.关键词
卷积神经网络/移动终端/物品识别/预训练模型Key words
Convolutional neural network/Mobile terminal/Object recognition/Pre-trained model分类
信息技术与安全科学引用本文复制引用
严圣军,吴谨..基于卷积神经网络的物品识别系统设计与实现[J].计算机应用与软件,2017,34(11):109-112,118,5.
