计算机工程与应用2019，Vol.55Issue(13)：212-217,6.DOI:10.3778/j.issn.1002-8331.1804-0057
具备高层语义特征的离散哈希图像检索算法
Discrete Hash Image Retrieval Algorithm with High-Level Semantic Features
DUAN Wenjing 1CHEN Shaoping1
作者信息
- 1. School of Science, Wuhan University of Technology, Wuhan 430070, China
- 折叠
摘要
Abstract
Deep Hash has been applied in the field of image search very well. However, the previous deep Hash method has the limitation that the semantic information is not fully utilized. This paper, develops a discrete Hash algorithm based on deep supervision, assuming that learning binary code should be an ideal choice of classification. The pair tag information and classified information are used to learn Hash codes within a framework. The output of the last layer is restricted to binary code directly. Due to the discrete properties of Hash codes, the alternate minimization method is used to optimize the target function. The proposed algorithm is proved to be better than the other supervised Hash methods in three image retrieval databases CIFAR-10,NUS-WIDE and SUN397.关键词
离散哈希/图像检索/深度学习Key words
discrete Hash/ image retrieval/ deep learning分类
信息技术与安全科学引用本文复制引用
DUAN Wenjing,CHEN Shaoping..具备高层语义特征的离散哈希图像检索算法[J].计算机工程与应用,2019,55(13):212-217,6.
