Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Version 1.0.0.0 (144 MB) by
Kai Zhang
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
This is the testing demo of the paper "Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising".
There are two kinds of models, including specific/blind models for Gaussian denoising and a single model for Gaussian denoising, single image super-resolution (SISR) and JPEG image deblocking.
Cite As
Kai Zhang (2024). Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising (https://github.com/cszn/DnCNN), GitHub. Retrieved .
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- Image Processing and Computer Vision > Computer Vision Toolbox > Recognition, Object Detection, and Semantic Segmentation >
- AI, Data Science, and Statistics > Deep Learning Toolbox > Get Started with Deep Learning Toolbox >
- Parallel Computing > Parallel Computing Toolbox > Big Data Processing >
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TrainingCodes/DnCNN_TrainingCodes_DagNN_v1.1
TrainingCodes/DnCNN_TrainingCodes_DagNN_v1.1/utilities
TrainingCodes/DnCNN_TrainingCodes_v1.0
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TrainingCodes/DnCNN_TrainingCodes_v1.0/data/utilities
TrainingCodes/DnCNN_TrainingCodes_v1.1
TrainingCodes/DnCNN_TrainingCodes_v1.1/data
TrainingCodes/DnCNN_TrainingCodes_v1.1/data/utilities
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Version | Published | Release Notes | |
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1.0.0.0 |
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To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.