  Content based providers transmits real time complex signal such as video data
from one region to another. During this transmission process, the signals
usually end up distorted or degraded where the actual information present in
the video is lost. This normally happens in the streaming video services
applications. Hence there is a need to know the level of degradation that
happened in the receiver side. This video degradation can be estimated by
network state parameters like data rate and packet loss values. Our proposed
solution vQoS GAN (video Quality of Service Generative Adversarial Network) can
estimate the network state parameters from the degraded received video data
using a deep learning approach of semi supervised generative adversarial
network algorithm. A robust and unique design of deep learning network model
has been trained with the video data along with data rate and packet loss class
labels and achieves over 95 percent of training accuracy. The proposed semi
supervised generative adversarial network can additionally reconstruct the
degraded video data to its original form for a better end user experience.
