Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 10
3197-3200

Feature relevance fusion based deep hashing for image representation

Zhu Jie1
Zhang Nannan1
Liu Taihang1
Liu Bo2
Wu Shufang3
1. Dept. of Information Management, National Police University for Criminal Justice, Baoding Hebei 071000, China
2. College of Information Science & Technology, Hebei Agricultural University, Baoding Hebei 071000, China
3. College of Management, Hebei University, Baoding Hebei 071000, China
DOI: 10.19734/j.issn.1001-3695.2019.06.0169

Abstract

This paper studied problem that the deep descriptors cannot provide the correlation between the features. This paper proposed a feature relevance fusion based deep hashing method to incorporate the relationship between different deep descriptors into the description of the image contents. Firstly, it extracted the feature maps from the pre-trained network and used for deep descriptor generation. Then, it mapped these descriptors to deep visual words, and also explored the frequent item set based on these deep visual words. Next, it concatenated deep visual words based image representation of discrete values and frequent item set based image representation of binary values to represent an image. Finally, it formulated an optimization based on the intra-class and inter-class similarities between images to obtain the optimal thresholds to convert the image representation into a binary string. Extensive experiments show that compared with some state-of-the-art methods, the proposed method can achieve satisfying retrieval performance in the holiday, Oxford and Paris image databases.

Foundation Support

国家社会科学基金资助项目(17BTQ068)
河北省自然科学基金资助项目(F2018511002,G2018204093)
河北省高等学校科学技术研究项目(Z2019037)
中央司法警官学院校级科研项目(XYZ201602)
河北大学中西部提升综合实力专项
河北省高等学校科学研究项目青年基金资助项目(QN2018084)
河北农业大学校理工基金资助项目(LG201804)
河北农业大学自主培养人才科研专项资助项目(PY201810)
交通数据分析与挖掘北京市重点实验室开放课题

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.06.0169
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 10
Section: Technology of Graphic & Image
Pages: 3197-3200
Serial Number: 1001-3695(2020)10-065-3197-04

Publish History

[2020-10-05] Printed Article

Cite This Article

朱杰, 张楠楠, 刘太行, 等. 融合特征关联性的深度哈希图像表示方法 [J]. 计算机应用研究, 2020, 37 (10): 3197-3200. (Zhu Jie, Zhang Nannan, Liu Taihang, et al. Feature relevance fusion based deep hashing for image representation [J]. Application Research of Computers, 2020, 37 (10): 3197-3200. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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