Paper Title
AdaptiveGenerativeCompression:Anin-depth Exploration of GAN-Enhanced HEVC Video Compression for Improved QOS

Abstract
There has been increased demand for more immersive video content for a better Quality of Service. This prompted the need for newer compression algorithms which would retain or even improve the original video quality. This research specifically delves into the implementation of a lossless Generative Adversarial Network(GAN)-basedH.265videocompression.Themain employed methodsand applied treatments are briefly described. Subsequently, this work’s findings are presented in the results sections. The conclusions indicates the effectiveness of the (GAN)-based algorithm utilized in the video compression process. Keywords - HEVC; H.265; GAN; Machine Learning; Deep Learing; Artificial Inteligence; QOS)