生成对抗网络GAN的研究进展.

The significance of the GAN model based on the zero-sum game idea is that the data distribution can be obtained through unsupervised learning, and it can generate more realistic data. It can be applied in many fields, especially the field of computer vision, and achieved great results in image generation, so that it becomes a hot spot in current research. This paper took the GAN model and its application results in specific fields as the research object, conducted extensive research on the improvement and expansion of GAN research results, and discussed from multiple practical application areas such as image super- resolution reconstruction and text synthesis pictures . It systematically sorted out and summarized the advantages and disadvantages of GAN, predicted and analyzed the development trend and application prospect of GAN in combination with natural language processing and reinforcement learning. [ABSTRACT FROM AUTHOR]