Search Results for author:
Found 3 papers, 1 papers with code
Advanced Super-Resolution using Lossless Pooling Convolutional Networks
In this paper, we present a novel deep learning-based approach for still image super-resolution, that unlike the mainstream models does not rely solely on the input low resolution image for high quality upsampling, and takes advantage of a set of artificially created auxiliary self-replicas of the input image that are incorporated in the neural network to create an enhanced and accurate upscaling scheme.
Convolutional Neural Networks for Video Quality Assessment
Moreover, transmission also introduces delays and other distortion types which affect the perceived quality.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
