A Super Sampling model created using the SRCNN method proposed by Chao Dong, Chen Change Loy in 2015. It uses Convolutional Networks to identify features and uses "Depth-To-Feature" technique in the end to generate a high resolution image of a given low resolution input. The model is trained and tested on BSDS500 dataset.
