Search Results for author:
Found 2 papers, 1 papers with code
iiTransformer: A Unified Approach to Exploiting Local and Non-Local Information for Image Restoration
The goal of image restoration is to recover a high-quality image from its degraded input.
Ranked #3 on
Color Image Denoising
on Urban100 sigma25
Automatic Registration between Cone-Beam CT and Scanned Surface via Deep-Pose Regression Neural Networks and Clustered Similarities
The main significance of our study is twofold: 1) the employment of light-weighted neural networks which indicates the applicability of neural network in extracting pose cues that can be easily obtained and 2) the introduction of an optimal cluster-based registration method that can avoid metal artifacts during the matching procedures.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
