This is the Linux app named DnCNN whose latest release can be downloaded as DnCNNsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named DnCNN with OnWorks for free.
请按照以下说明运行此应用程序：
- 1. 在您的 PC 中下载此应用程序。
- 2. 在我们的文件管理器 https://www.onworks.net/myfiles.php?username=XXXXX 中输入您想要的用户名。
- 3. 在这样的文件管理器中上传这个应用程序。
- 4. 从此网站启动OnWorks Linux online 或Windows online emulator 或MACOS online emulator。
- 5. 从您刚刚启动的 OnWorks Linux 操作系统，使用您想要的用户名转到我们的文件管理器 https://www.onworks.net/myfiles.php?username=XXXXX。
- 6. 下载应用程序，安装并运行。
SCREENSHOTS
Ad
DnCNN
商品描述
This repository implements DnCNN (“Deep CNN Denoiser”) from the paper “Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising”. DnCNN is a feedforward convolutional neural network that learns to predict the residual noise (i.e. noise map) from a noisy input image, which is then subtracted to yield a clean image. This formulation allows efficient denoising, supports blind Gaussian noise (i.e. unknown noise levels), and can be extended to related tasks like image super-resolution or JPEG deblocking in some variants. The repository includes training code (using MatConvNet / MATLAB), demo scripts, pretrained models, and evaluation routines.
功能
- Residual learning (predicting noise rather than clean image)
- Batch normalization to stabilize training
- Single model handling multiple noise levels (blind denoising)
- Demo / test scripts included
- Pretrained model weights for ease of use
- Extensions to super-resolution / deblocking tasks
程式语言
MATLAB
分类
This is an application that can also be fetched from https://sourceforge.net/projects/dncnn.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
