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Found 6 papers, 5 papers with code
N2V2 -- Fixing Noise2Void Checkerboard Artifacts with Modified Sampling Strategies and a Tweaked Network Architecture
We validate our modifications on a range of microscopy and natural image data.
Fourier Image Transformer
Additionally, we show that an encoder-decoder setup can be used to query arbitrary Fourier coefficients given a set of Fourier domain observations.
DenoiSeg: Joint Denoising and Segmentation
Here we propose DenoiSeg, a new method that can be trained end-to-end on only a few annotated ground truth segmentations.
Leveraging Self-supervised Denoising for Image Segmentation
Deep learning (DL) has arguably emerged as the method of choice for the detection and segmentation of biological structures in microscopy images.
Noise2Void - Learning Denoising from Single Noisy Images
The field of image denoising is currently dominated by discriminative deep learning methods that are trained on pairs of noisy input and clean target images.
Cryo-CARE: Content-Aware Image Restoration for Cryo-Transmission Electron Microscopy Data
Cryo-transmission electron microscopy (cryo-TEM) could profoundly benefit from improved denoising methods, unfortunately it is one of the latter.
