Algorithm Research & Explore
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1689-1693

Multi-mode generative adversarial network

Yin Laiguo
Sun Rencheng
Shao Fengjing
Sui Yi
Xing Tongtong
Dept. of Computer Science & Technology, Qingdao University, Qingdao Shandong 266071, China

Abstract

Generative adversarial networks have become one of the most popular research directions in the field of deep learning. Its main advantage is that it can fit unknown distribution in an unsupervised way. At present, the generative adversarial network is valuable in the field of image generation. It can generate some high-quality images, but it also exposes some disadvantages. In the process of image generation, the problem of mode collapse often occurs, which leads to the generated sample being too single. To solve this problem, this paper improved the model structure and loss function of the generative adversarial network, so that the discriminator could measure the difference of distribution between generated data and real data from many aspects, thus increasing the diversity of generated samples. Experiments on multiple data sets show that the proposed model alleviates the mode collapse to a large extent.

Foundation Support

国家自然科学青年基金资助项目(41706198)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.10.0605
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 6
Section: Algorithm Research & Explore
Pages: 1689-1693
Serial Number: 1001-3695(2022)06-015-1689-05

Publish History

[2022-01-17] Accepted Paper
[2022-06-05] Printed Article

Cite This Article

尹来国, 孙仁诚, 邵峰晶, 等. 多模式生成对抗网络 [J]. 计算机应用研究, 2022, 39 (6): 1689-1693. (Yin Laiguo, Sun Rencheng, Shao Fengjing, et al. Multi-mode generative adversarial network [J]. Application Research of Computers, 2022, 39 (6): 1689-1693. )

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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