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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 5
1434-1440

Unsupervised ternary hash method based on contrastive learning

Li Yuqiang
Lu Ziwei
Liu Chun
School of Computer Science & Artificial Intelligence, Wuhan University of Technology, Wuhan 430070, China
DOI: 10.19734/j.issn.1001-3695.2022.09.0479

Abstract

To solve the problem of low retrieval accuracy of the existing unsupervised binary hashing method due to quantization loss, this paper proposed a new unsupervised ternary hash method based on contrastive learning refers to the CIBHash method——CUTHash, using ternary hash code for image retrieval. Specifically, the method used the contrastive learning framework of decoupled loss to acquire a compact and accurate feature representation for each sample. Then, to obtain the ternary hash codes, it used the smooth function after the feature representation which could solve the zero gradient problem caused by the quantification of discrete functions. Finally, the representation of the enhanced view of the same image after the application of improved contrastive loss could preserve the semantic information and improve the discriminative ability in the Hamming space. So that it can be better applied to unsupervised image retrieval tasks. It performed a large number of comparative experiments on the CIFAR-10, NUS-WIDE, MSCOCO, and ImageNet100 datasets, and achieved better retrieval performances than the current mainstream unsupervised hash method, thus verifying the effectiveness of the CUTHash method.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.09.0479
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 5
Section: Algorithm Research & Explore
Pages: 1434-1440
Serial Number: 1001-3695(2023)05-023-1434-07

Publish History

[2022-12-05] Accepted Paper
[2023-05-05] Printed Article

Cite This Article

李玉强, 陆子微, 刘春. 基于对比学习的无监督三元哈希方法 [J]. 计算机应用研究, 2023, 40 (5): 1434-1440. (Li Yuqiang, Lu Ziwei, Liu Chun. Unsupervised ternary hash method based on contrastive learning [J]. Application Research of Computers, 2023, 40 (5): 1434-1440. )

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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