计算机中生成式对抗网络的研究进展及展望

Research progress and prospect of generative countermeasure network in computer

生成对抗网络(GAN)作为一种深层次的计算机学习模型,已经成为近年来神经网络领域中非常具有发展前景的一项技术模型,本文通过对相关文献的整理和查阅,首先简述了原始的生成对抗网络的组成以及其相关特征,随后基于原始网络的一些严重缺陷介绍了相关的改进网络的优化方法,最终对整篇论文进行总结,并对未来的发展进行了展望。

Generate countermeasures network(GAN,Generative Adversarial Networks)is a kind of deep-seated computer learning model,which has become a very promising technical model in the field of neural network in recent years.Through the collation and integration of relevant literature,this paper first described the composition and relevant characteristics of the original generative countermeasure network,and then introduced the relevant optimization methods of the improved network based on some serious defects of the original network.Finally,we summarize the whole paper and look forward to the future.