What is it about?
In this work various architectures of convolutional neural networks which are used for image denoising are explained . The comparative performance analysis of various images corrupted with gaussian noise is compiledin terms of PSNR.
Featured Image
Why is it important?
Our findings can help to explore the architecture of convolutional neural networks for image denoising. The advantages and disadvantages of various networks gives insights for further research that can be done.
Read the Original
This page is a summary of: State-of-Art Analysis of Image Denoising Methods using Convolutional Neural Networks, IET Image Processing, August 2019, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/iet-ipr.2019.0157.
You can read the full text:
Contributors
The following have contributed to this page
