Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 6
1734-1738

Domain adaptation based on weighted classification loss and nuclear-norm

Du Shelin
Huang Binghe
Li Rongpeng
Song Xueli
Xiao Yuzhu
School of Science, Chang'an University, Xi'an 710064, China
DOI: 10.19734/j.issn.1001-3695.2022.10.0514

Abstract

Domain adaptation transfers the knowledge learned from the source domain to the target domain, so that the model can be effectively trained in the case of less labeled data. The domain adaptation models using pseudo-labels do not consider the influence of false pseudo-labels, and the classification accuracy of samples at the decision boundary is low. For the above problems, this paper proposed domain adaptation model based on weighted classification loss and nuclear-norm. The model used confident sample features and their pseudo-labels, and constructed an auxiliary domain with the source domain sample features with real labels. It designed a weighted classification loss function on the auxiliary domain reduced the influence of false labels in the training process. Batch nuclear-norm maximization loss improved the accuracy of sample pseudo-labels at the decision boundary. The comparison experiments with previous models on the benchmark datasets of Office31, Office-Home and Image-CLEFDA illustrate that this method has higher accuracy.

Foundation Support

长安大学中央高校基本科研业务费专项资金资助项目(310812163504)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.10.0514
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 6
Section: Algorithm Research & Explore
Pages: 1734-1738
Serial Number: 1001-3695(2023)06-021-1734-05

Publish History

[2023-01-05] Accepted Paper
[2023-06-05] Printed Article

Cite This Article

杜社林, 黄炳赫, 李荣鹏, 等. 基于加权分类损失和核范数的领域自适应模型 [J]. 计算机应用研究, 2023, 40 (6): 1734-1738. (Du Shelin, Huang Binghe, Li Rongpeng, et al. Domain adaptation based on weighted classification loss and nuclear-norm [J]. Application Research of Computers, 2023, 40 (6): 1734-1738. )

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.

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