activity
20162020
most citedQuality Aware Generative Adversarial Networks

18 citations · 18 across the 2 of their papers we have counts for

collaborators

8 papers

cs.GR2020

Deep No-reference Tone Mapped Image Quality Assessment

Chandra Sekhar Ravuri, Rajesh Sureddi, Sathya Veera Reddy Dendi +2

The process of rendering high dynamic range (HDR) images to be viewed on conventional displays is called tone mapping. However, tone mapping introduces distortions in the final ima…

cs.CV201918 cited

Quality Aware Generative Adversarial Networks

Parimala Kancharla, Sumohana S. Channappayya

Generative Adversarial Networks (GANs) have become a very popular tool for implicitly learning high-dimensional probability distributions. Several improvements have been made to th…

cs.MM2018

Streaming Video QoE Modeling and Prediction: A Long Short-Term Memory Approach

Nagabhushan Eswara, S Ashique, Anand Panchbhai +5

HTTP based adaptive video streaming has become a popular choice of streaming due to the reliable transmission and the flexibility offered to adapt to varying network conditions. Ho…

eess.SP2018

Novel Light Weight Compressed Data Aggregation Using Sparse Measurements for IoT Networks

Amarlingam M, Pradeep Kumar Mishra, P Rajalakshmi +2

Optimal data aggregation aimed at maximizing IoT network lifetime by minimizing constrained on-board resource utilization continues to be a challenging task. The existing data aggr…

cs.MM2018

Modeling Continuous Video QoE Evolution: A State Space Approach

Nagabhushan Eswara, Hemanth P. Sethuram, Soumen Chakraborty +3

A rapid increase in the video traffic together with an increasing demand for higher quality videos has put a significant load on content delivery networks in the recent years. Due…

eess.IV2018

Estimating Depth-Salient Edges And its Application To Stereoscopic Image Quality Assessment

Sameeulla Khan Md, Sumohana Channappayya

The human visual system pays attention to salient regions while perceiving an image. When viewing a stereoscopic 3D (S3D) image, we hypothesize that while most of the contribution…