Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 3
932-935

Image classification algorithm based on feature recalibration GAN

Jiang Daihong1
Zhang Sanyou2,3
Liu Qikai3
1. School of Information & Electronic Engineering, Xuzhou Institute of Technology, Xuzhou Jiangsu 221008, China
2. Dept. of Science & Technology, Suzhou Wujiang District Public Security Bureau, Suzhou Jiangsu 215200, China
3. School of Information & Electrical Engineering, China University of Mining & Technology, Xuzhou Jiangsu 221008, China
DOI: 10.19734/j.issn.1001-3695.2018.08.0668

Abstract

In view of the loss strategy and structure of traditional discriminator is difficult to extract more abstract and task related robustness features, which leads to the shortage of semi supervised image classification, this paper proposed a generation countermeasure network based on feature recalibration. In order to learn the related features of the task, on the basis of the existing semi supervised GAN, it introduced the unsupervised canonical loss regular term of the model under different states to the discriminator, and the different output of the same input corresponding to the two branches of the training sample was punished to guide the optimization direction of the feature recalibration. In addition, it added the compression activation module to the discriminator to optimize the convolution pool structure of the traditional discriminator. The module automatically learned the importance of each characteristic channel, and could extract the features related to the task to suppress the unrelated features of the task, and realized the recalibration function of the feature, thus improving the performance of the semi-supervised image classification.

Foundation Support

国家自然科学基金资助项目(61379100)
江苏省高等学校自然科学研究重大项目(18KJA520012)
徐州市科技计划基金资助项目(KC19197)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.08.0668
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 3
Section: Technology of Graphic & Image
Pages: 932-935
Serial Number: 1001-3695(2020)03-065-0932-04

Publish History

[2020-03-05] Printed Article

Cite This Article

姜代红, 张三友, 刘其开. 基于特征重标定生成对抗网络的图像分类算法 [J]. 计算机应用研究, 2020, 37 (3): 932-935. (Jiang Daihong, Zhang Sanyou, Liu Qikai. Image classification algorithm based on feature recalibration GAN [J]. Application Research of Computers, 2020, 37 (3): 932-935. )

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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.

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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