noise2noise

There are 2 repositories under noise2noise topic.

• yu4u / noise2noise

  An unofficial and partial Keras implementation of "Noise2Noise: Learning Image Restoration without Clean Data"

  convolutional-neural-networksdeep-learningdenoisingkerasnoise2noise
  Language:Python 1066

• madhavmk / Noise2Noise-audio_denoising_without_clean_training_data

  Source code for the paper titled "Speech Denoising without Clean Training Data: a Noise2Noise Approach". Paper accepted at the INTERSPEECH 2021 conference. This paper tackles the problem of the heavy dependence of clean speech data required by deep learning based audio denoising methods by showing that it is possible to train deep speech denoising networks using only noisy speech samples.

  speech-denoisingaudio-denoisingspeech-enhancementaudio-enhancementnoise-reductionnoise-removalnoise2noisedeep-learningautoencoderdata-collectionspeech
  Language:Jupyter Notebook 162

• shivamsaboo17 / Deep-Restore-PyTorch

  Deep CNN for learning image restoration without clean data!

  noise-reductiondeep-learningsrresnetnvdianoise2noisegaussian-noisecorrupt-text-removalpytorch
  Language:Jupyter Notebook 65

• ZhenyuTan / Noise2Noise-Cryo-EM-image-denoising

  pytorch implementation of noise2noise for Cryo-EM image denoising

  cryo-emnoise2noisedeep-learning
  Language:Python 40

• hanyoseob / pytorch-noise2noise

  Noise2Noise: Learning Image Restoration without Clean Data

  deep-learningdeep-neural-networksunsupervised-learningnoise2noisecnnpytorch-gan
  Language:Python 12

• johnPertoft / noise2noise

  Noise2Noise implementation

  noise2noisetensorflow
  Language:Python 3

• MPI-Dortmund / sphire-janni

  Just another noise 2 noise implementation (JANNI) with Keras

  deep-learningnoise2noisekerassphire
  Language:Jupyter Notebook 2
• Noise2Noise-Lite-two-ligther-versions-of-the-famous-AI-denoiser-for-small-images

  EliaFantini / Noise2Noise-Lite-two-ligther-versions-of-the-famous-AI-denoiser-for-small-images

  Noise2Noise is an AI denoiser trained with noisy images only. We implemented a ligther version which trains faster on smaller pictures without losing performance and an even simpler one where every low-level component was implemented from scratch, including a reimplementation of autograd.

  2d-convolutionadam-optimizerautogradautograd-enginedenoiserdenoiser-networkmean-square-errornoise-reductionnoise2noisepythonpytorchpytorch-frameworkpytorch-implementationrelu-activationsigmoid-functionunetsequential-pytorch
  Language:Jupyter Notebook 1

• PINTO0309 / noise2noise

  An unofficial and partial Keras implementation of "Noise2Noise: Learning Image Restoration without Clean Data" (AI can now fix your grainy photos by only looking at grainy photos. Noise2Noise)

  noise2noisedeep-learningconvolutional-neural-networksdenoisingkeraspythonnvidiagrainy-photos
  Language:Python 1

• the-pinbo / image-denoising

  The standard approach to image reconstruction using deep learning is to use clean image priors for training purposes. In this project, we attempt to achieve denoising without using a clean image prior and yet, achieving a performance comparable to, or sometimes, even better than that obtained using the conventional approach.

  autoencoderdatasetdenoisingdenoising-autoencodersgaussian-noiseimage-data-generatorimage-processingimage-restorationnoise2noiserednettensorflowunetbsd500
  Language:Jupyter Notebook 0