An Image Retrieval Algorithm Based on Multiple Convolutional Features of RPN and Weighted Cosine Similarity

被引：0

作者：

Liu, Xinhua ^{[1
,2
]}

Hu, Gaoqiang ^{[1
,2
]}

Ma, Xiaolin ^{[1
,2
]}

Kuang, Hailan ^{[1
,2
]}

机构：

[1] Wuhan Univ Technol, Sch Informat Engn, Wuhan, Peoples R China

[2] Wuhan Univ Technol, Key Lab Fiber Opt Sensing Technol & Informat Proc, Minist Educ, Wuhan, Peoples R China

来源：

PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC) | 2018年

关键词：

Feature Extraction; Deep Learning; Weighted Cosine Similarity; Image Retrieval;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Aiming at solving the difficulty of feature selecting and the poor retrieval result in the image retrieval, we proposed an image retrieval algorithm which was based on multiple convolutional features of RPN and weighted cosine similarity. We used the deep learning network RPN to extract the multiple convolutional features; and ranked the images by the weighted cosine similarity we proposed. To validate this algorithm; we used Oxford Buildings 5k and Paris Buildings 6k as two image retrieval datasets. As a result, our algorithm improved the mAP by 3% similar to 6% and had better retrieval and ranking results.

引用

页码：4095 / 4098

页数：4

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