Generative Adversarial Networks for Image Super-Resolution: A Survey
NeutralArtificial Intelligence
- A recent survey on Generative Adversarial Networks (GANs) for Single Image Super-Resolution (SISR) highlights the advancements in image processing, focusing on various GAN implementations and their comparative performance on public datasets. The study emphasizes the lack of comprehensive literature summarizing these developments, which are crucial for enhancing low-resolution images.
- This survey is significant as it consolidates knowledge on GANs, providing insights into their optimization methods and learning approaches, which can guide future research and applications in image enhancement.
- The exploration of GANs in SISR reflects a broader trend in artificial intelligence, where innovative models like the Individualized Exploratory Transformer and Mixture-of-Experts frameworks are emerging to improve efficiency and quality in image processing, indicating a dynamic evolution in the field.
— via World Pulse Now AI Editorial System
