Applied and Computational Engineering
- The Open Access Proceedings Series for Conferences
Proceedings of the 4th International Conference on Computing and Data Science (CONF-CDS 2022)
Series Vol. 2 , 22 March 2023
Open
Access | Article
Research on Image Generation Methods Based on Adversarial Neural Networks
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Abstract
Image generation has become a heated research topic in recent years owing to its wide landing scenes and great potential in all walks of life. Especially after the emergence of adversarial neural networks, both the training process and results have been greatly improved compared with previous model methods. This paper focuses on the advantages of directly using Generative Adversarial Nets (GAN) to generate images, as well as its main problems: training instability, pattern collapse, and global correlation, and introduces the strategies and skills of subsequent improved GAN for these problems. Through experiments, we compare the improved network with the original GAN and try to combine the core strategies of these networks. In the experiment, the image quality generated by the combined network is higher.
Keywords
WGAN, adversarial neural networks, Image generation, SAGAN
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 4th International Conference on Computing and Data Science (CONF-CDS 2022)
- ISBN (Print)
- 978-1-915371-19-5
- ISBN (Online)
- 978-1-915371-20-1
- Published Date
- 22 March 2023
- Series
- Applied and Computational Engineering
- ISSN (Print)
- 2755-2721
- ISSN (Online)
- 2755-273X
- DOI
- 10.54254/2755-2721/2/20220590
- Copyright
- 22 March 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited