Search Results for author:
Found 4 papers, 2 papers with code
VisGraphNet: a complex network interpretation of convolutional neural features
Here we propose and investigate the use of visibility graphs to model the feature map of a neural network.
Gated Multiple Feedback Network for Image Super-Resolution
The rapid development of deep learning (DL) has driven single image super-resolution (SR) into a new era.
Ranked #18 on
Image Super-Resolution
on BSD100 - 4x upscaling
A Symmetric Encoder-Decoder with Residual Block for Infrared and Visible Image Fusion
For the fusion stage, first, the trained model is utilized to extract the intermediate features and compensation features of two source images.
Feedback Network for Image Super-Resolution
In this paper, we propose an image super-resolution feedback network (SRFBN) to refine low-level representations with high-level information.
