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 NetworksOA

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

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

Deep convolution generative adversarial network (DCGAN)deep learningguided generative adversarial network (GAN)visualization

Deep convolution generative adversarial network (DCGAN)deep learningguided generative adversarial network (GAN)visualization

《电子科技学刊》 2022 (1)

70-80,11

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

10.11989/JEST.1674-862X.90501106

评论

您当前未登录!去登录点击加载更多...