Topic: "denoising-algorithm"
liv-group/reproducible-video-denoising-state-of-the-art
Collection of popular and reproducible video denoising works.
Size: 4.88 KB - Last synced at: almost 2 years ago - Pushed at: over 5 years ago - Stars: 98 - Forks: 12
Novartis/scar
scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics
Language: Python - Size: 60 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 44 - Forks: 4
samuelstjean/nlsam
The reference implementation for the Non Local Spatial and Angular Matching (NLSAM) denoising algorithm for diffusion MRI
Language: Python - Size: 63.3 MB - Last synced at: 11 days ago - Pushed at: 11 days ago - Stars: 24 - Forks: 11
archana1998/compressive-sensing-denoising
Compressed sensing and denoising of images using sparse representations
Language: MATLAB - Size: 20.3 MB - Last synced at: 12 months ago - Pushed at: almost 5 years ago - Stars: 23 - Forks: 9
weblineindia/AIML-Image-Enhancement
AI ML based Image enhancement module built in Python. It is used for improving the quality of images using different filters in openCV. It works better with gray-scale images.
Language: Python - Size: 242 KB - Last synced at: 2 months ago - Pushed at: over 1 year ago - Stars: 15 - Forks: 3
matthieumeo/pyoneer
Pyoneer is a Python 3 package for the continuous recovery of non-bandlimited periodic signals with finite rates of innovation (e.g. Dirac streams) from generalised measurements.
Language: Python - Size: 4.82 MB - Last synced at: 20 days ago - Pushed at: over 4 years ago - Stars: 10 - Forks: 2
mdb0/ocaml_rtx
Language: OCaml - Size: 6.49 MB - Last synced at: about 1 year ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 0
fork123aniket/Denoising-Diffusion-Probabilistic-Model-from-Scratch
Implementation of Denoising Diffusion Probabilistic Model from Scratch for Image Generation Task in PyTorch
Language: Python - Size: 617 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0
