In this chapter, we began by introducing SRGANs. Then, we looked at the architecture of the generator and discriminator networks. Later, we carried out the required setup for the project. Then, we gathered and explored the dataset. After that, we implemented the project in Keras before training the SRGAN, evaluating the trained SRGAN network, and optimizing the trained model using hyperparameter optimization techniques. Finally, we took a brief look at some different applications of SRGANs.
In the next chapter, we will be going through StackGAN and its different applications.