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Technology of Graphic & Image
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628-632

Text-guided adversarial hashing for cross-modal retrieval

Zhu Jie
Dept. of Information Management, National Police University for Criminal Justice, Baoding Hebei 071000, China

Abstract

With the development of deep learning, cross-modal hashing retrieval methods have made considerable progress. However, current cross-modal hashing retrieval methods are usually based on two hypotheses, a similar pair of texts can have similar images, the images with the same category are globally similar to each other. However, the data in the real-world data set often fails to meet the above two hypotheses, which leads to the decrease of retrieval performance. This paper proposed a TAH. TAH used the text hash code to train the image network, and used the combination of the local and global image features to represent the images. In addition, it proposed the text intra-modality global consistency loss, inter-modality local, global consistency loss and adversarial classification loss to train the cross-modal network. Experiments show that TAH can achieve satisfactory retrieval performance in three data sets.

Foundation Support

中央司法警官学院博士科研启动经费专项项目(BSQDS202103)
河北省教育厅人文社科重大攻关资助项目(ZD202102)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.07.0222
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 2
Section: Technology of Graphic & Image
Pages: 628-632
Serial Number: 1001-3695(2022)02-054-0628-05

Publish History

[2021-10-08] Accepted Paper
[2022-02-05] Printed Article

Cite This Article

朱杰. 基于文本引导对抗哈希的跨模态检索方法 [J]. 计算机应用研究, 2022, 39 (2): 628-632. (Zhu Jie. Text-guided adversarial hashing for cross-modal retrieval [J]. Application Research of Computers, 2022, 39 (2): 628-632. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


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