Generative Adversarial Network and Its Research Progress in Image Generation
Generative adversarial networks (GAN) has become a popular research direction in the field of deep learning. The unique adversarial idea of GAN comes from the two-player zero-sum game in game theory. How to solve the problems of unstable GAN training, poor quality of generated samples, inadequate ev...
Main Author: | MA Yongjie, XU Xiaodong, ZHANG Ru, XIE Yirong, CHEN Hong |
---|---|
Format: | Article |
Language: | zho |
Published: |
Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
2021-10-01
|
Series: | Jisuanji kexue yu tansuo |
Subjects: | |
Online Access: | http://fcst.ceaj.org/CN/abstract/abstract2906.shtml |
Similar Items
-
Recent Progress on Generative Adversarial Networks (GANs): A Survey
by: Zhaoqing Pan, et al.
Published: (2019-01-01) -
Generative Adversarial Networks GAN Overview
by: LIANG Junjie, WEI Jianjing, JIANG Zhengfeng
Published: (2020-01-01) -
Applications of Generative Adversarial Networks in Medical Image Translation
by: Xiao CHANG, et al.
Published: (2022-09-01) -
Exploring generative adversarial networks and adversarial training
by: Afia Sajeeda, et al.
Published: (2022-06-01) -
A pavement crack synthesis method based on conditional generative adversarial networks
by: Hui Yao, et al.
Published: (2024-01-01)