Assessment of an unsupervised denoising approach based on Noise2Void in digital mammography
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-19499-1
Abstract: Full-field digital mammography (FFDM) is the most common imaging technique for breast cancer screening programs. Still, it is limited by noise from quantum effects, electronic issues, and X-ray scattering, affecting the image quality. Traditional denoising… read more here.
Keywords: digital mammography; unsupervised denoising; assessment unsupervised; denoising approach ... See more keywords
Unsupervised Denoising for Super-Resolution (UDSR) of Real-World Images
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3223101
Abstract: Single Image Super-Resolution (SISR) using Convolutional Neural Networks (CNNs) for many applications in supervised manner has resulted in significant improvement in state-of-the-art performance. Such supervised models achieve remarkable accuracy; albeit their poor generalization ability for… read more here.
Keywords: unsupervised denoising; real world; image; super resolution ... See more keywords
Optimal Transport for Unsupervised Denoising Learning.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2022.3170155
Abstract: Recently, much progress has been made in unsupervised denoising learning. However, existing methods more or less rely on some assumptions on the signal and/or degradation model, which limits their practical performance. How to construct an… read more here.
Keywords: microscopy; supervised methods; unsupervised denoising; denoising learning ... See more keywords