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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 5
1357-1361

Pseudo label based unsupervised domain adaptation classification method

Yang Guoqing1
Guo Benhua1,2
Qian Shuqu2
Wu Huihong2
Han Jing2
1. College of Information, Guizhou University of Finance & Economics, Guiyang 550025, China
2. College of Mathematics & Computer Science, Anshun University, Anshun Guizhou 561000, China
DOI: 10.19734/j.issn.1001-3695.2021.10.0442

Abstract

Existing domain-adaptive methods do not fully consider the pseudo-label confidence or pseudo-label loss calculation problems when matching distributions. To solve this problem, this paper proposed a cycle selection pseudo-label classification model(CSPL). It enhanced the training data by extracting image features using a depth network and labeling the target domain with a high confidence pseudo-label. It used MMD distance measurement to align the probability distributions of the source and target domains, and designed pseudo-label loss for iterative learning synchronously. It updated the model as the training model for the next cycle until the model converges. A large number of experiments on the frequently-used domain adaptation data sets on Office31, Office-Home, ImageCLEF-DA and Amazon-Review show that the accuracy of the proposed model is improved by 4%~8% on average and robustness is also significantly increased compared with previous domain adaptation models.

Foundation Support

贵州省JMRH集成攻关大平台资助项目
国家自然科学基金资助项目(61762001)
贵州省教育厅创新群体重大项目(黔教合KY字［2018］034,［2019］069)
贵州省教育厅自然科学基金资助项目
青年科技人才成长项目(黔教合KY字［2020］131,［2018］337)
安顺学院研究生创新基金资助项目(asxyyjscx202104)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.10.0442
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 5
Section: Algorithm Research & Explore
Pages: 1357-1361
Serial Number: 1001-3695(2022)05-012-1357-05

Publish History

[2021-12-17] Accepted Paper
[2022-05-05] Printed Article

Cite This Article

杨国庆, 郭本华, 钱淑渠, 等. 基于伪标签的无监督领域自适应分类方法 [J]. 计算机应用研究, 2022, 39 (5): 1357-1361. (Yang Guoqing, Guo Benhua, Qian Shuqu, et al. Pseudo label based unsupervised domain adaptation classification method [J]. Application Research of Computers, 2022, 39 (5): 1357-1361. )

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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