Research on Image Recognition Technology Based on Convolution Neural Network

被引：2
|
作者：
Wang Jinghe [1 ]
机构：
[1] Hong Kong Univ Sci & Technol, Hong Kong, Peoples R China
来源：
2019 4TH INTERNATIONAL WORKSHOP ON MATERIALS ENGINEERING AND COMPUTER SCIENCES (IWMECS 2019) | 2019年
关键词：
Image recognition; Accuracy rate; Convolution neural network;
D O I：
10.25236/iwmecs.2019.028
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, the convolution neural network structure is used for image recognition. The initialized image is convoluted with the convolution core in the convolution layer to extract the features of the image. The extracted image features are compressed by the pooling layer by the full connection layer. The convolution neural network iterates the image for several times and compresses the image layer by layer to recognize the image and output the recognized image. Experiments show that compared with BP neural network, the network structure can significantly improve the accuracy of image recognition.
引用
收藏
页码：147 / 151
页数：5
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