Image Retrieval Algorithm based on Convolutional Neural Network

被引：0
|
作者：
Huang, Wen-qing [1 ]
Wu, Qiang [1 ]
机构：
[1] Zhejiang Sci Tech Univ, Sch Informat Sci & Technol, Hangzhou, Peoples R China
来源：
CURRENT TRENDS IN COMPUTER SCIENCE AND MECHANICAL AUTOMATION, VOL 1 | 2017年
关键词：
image retrieval; Convolutional Neural Network; feature extraction; Cosine Similarity;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
A convolutional neural network (CNN) is a kind of artificial neural network. It is widely used in image recognition and other fields because of its advantages in weight sharing. An image retrieval algorithm based on CNN is proposed in this paper. Firstly, the image is input into a pre-trained CNN, and the features of an image are extracted and normalized. Then the target image is matched with the feature base image, and the result of matching is sorted by means of cosine similarity method. Finally, the top 36 images are displayed according to the result of sorting. Experimental results show that our approach can improve the accuracy of image retrieval compared with the traditional image retrieval algorithm.
引用
收藏
页码：304 / 314
页数：11
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