Technology of Graphic & Image
|
591-594,599

Semi-supervised domain adaptation method based on dropout regularization

Li Zhihenga,b
He Juna,b
Hu Zhaohuaa
a. School of Electronics & Information Engineering, b. School of Artificial Intelligence, Nanjing University of Information Science & Technology, Nanjing 210044, China

Abstract

Aiming at the problem of inconsistent probability distribution between training samples and test samples in machine learning, this paper proposed a semi-supervised domain adaptation method based on dropout regularization to transfer neural representations from label-rich source domains to unlabeled target domains. From the perspective of semi-supervised learning, this paper added a small amount of labeled target domain data into the source domain data, so that the neural network could learn the feature distribution of target domain data while learning the feature distribution of source domain data. With the gui-dance of prior knowledge, neural network could fit target domain data well even without abundant label information. Experiments show that the proposed algorithm is superior to other existing algorithms in domain adaptation performance on digital datasets and robust on real datasets covering a wide range of natural categories.

Foundation Support

国家自然科学基金资助项目(61601230)
江苏省自然科学基金资助项目(BK20141004)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.11.0650
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 2
Section: Technology of Graphic & Image
Pages: 591-594,599
Serial Number: 1001-3695(2021)02-053-0591-04

Publish History

[2021-02-05] Printed Article

Cite This Article

李志恒, 何军, 胡昭华. 基于dropout正则化的半监督域自适应方法 [J]. 计算机应用研究, 2021, 38 (2): 591-594,599. (Li Zhiheng, He Jun, Hu Zhaohua. Semi-supervised domain adaptation method based on dropout regularization [J]. Application Research of Computers, 2021, 38 (2): 591-594,599. )

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  • 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.

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