Paper Contents
Abstract
This paper explores the integration of edge computing and cloud platforms in enhancing the performance of Generative Adversarial Networks (GANs) for image synthesis. As GANs demand high computational power and memory, leveraging the distributed nature of cloud and edge computing enables faster processing, lower latency, and scalable solutions. The paper discusses the advantages of combining edge computing's proximity to data sources with the cloud's high computational capacity to facilitate real-time image generation and improve the efficiency of GAN models. Moreover, the integration of these two technologies opens up new opportunities for applications in areas such as healthcare, autonomous systems, and augmented reality. The study provides a comprehensive analysis of the challenges, solutions, and future directions for the synergy between edge computing and cloud in the context of GAN-based image synthesis.
Copyright
Copyright © 2025 Biswanath Saha. This is an open access article distributed under the Creative Commons Attribution License.
