arXiv:2006.14319
공식 코드 · Papers with Code
Deep Learning for Cornea Microscopy Blind Deblurring
원문 초록
The goal of this project is to build a deep-learning solution that deblurs cornea scans, used for medical examination. The spherical shape of the eye prevents ophtamologist from having completely sharp image. Provided with a stack of corneas from confocal images, our approach is to build a model that performs an upscaling of the images using an SR (Super Resolution) Network.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
EAMamba: Efficient All-Around Vision State Space Model for Image Restoration
R3eVision: A Survey on Robust Rendering, Restoration, and Enhancement for 3D Low-Level Vision
Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching
Plug-and-Play Linear Attention for Pre-trained Image and Video Restoration Models
Deep Learning-Driven Ultra-High-Definition Image Restoration: A Survey
UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights
토론
이 논문과 연결된 포럼 글이 아직 없습니다.