首页|期刊导航|电子科技学刊|Exploration of the Relation between Input Noise and Generated Image in Generative Adversarial Networks

Exploration of the Relation between Input Noise and Generated Image in Generative Adversarial Networks

Hao-He Liu Si-Qi Yao Cheng-Ying Yang Yu-Lin Wang

电子科技学刊2022，Vol.20Issue(1)：70-80,11.

电子科技学刊2022，Vol.20Issue(1)：70-80,11.DOI:10.11989/JEST.1674-862X.90501106

Exploration of the Relation between Input Noise and Generated Image in Generative Adversarial Networks

Hao-He Liu ¹Si-Qi Yao ²Cheng-Ying Yang ³Yu-Lin Wang⁴

作者信息

1. School of Computer Science, Northwestern Polytechnical University, Xi'an 710072
2. International Institute of Service Engineering, Hangzhou Normal University, Hangzhou 311121
3. Department of Computer Science, University of Taipei, Taipei 10048
4. Shenzhen Research Institute, Wuhan University, Shenzhen 518057
折叠

摘要

关键词

Deep convolution generative adversarial network (DCGAN)/deep learning/guided generative adversarial network (GAN)/visualization

Key words

Deep convolution generative adversarial network (DCGAN)/deep learning/guided generative adversarial network (GAN)/visualization

引用本文复制引用

Hao-He Liu,Si-Qi Yao,Cheng-Ying Yang,Yu-Lin Wang..Exploration of the Relation between Input Noise and Generated Image in Generative Adversarial Networks[J].电子科技学刊,2022,20(1):70-80,11.

基金项目

This work was supported by Shenzhen Science and Technology Innovation Committee under Grants No. JCYJ20170306170559215 and No. JCYJ20180302153918689. （）

电子科技学刊

OACSCD

ISSN：1674-862X

访问量4

下载量0

段落导航