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15 search results found

Reproducible Image Denoising State Of The Art ⭐ 1,759

Collection of popular and reproducible image denoising works.

Qualityscaler ⭐ 1,519

QualityScaler - image/video AI upscaler app

Tensorflow 2.x implementation of the DTLN real time speech denoising model. With TF-lite, ONNX and real-time audio processing support.

Framework Reproducibility ⭐ 410

Providing reproducibility in deep learning frameworks

Realscaler ⭐ 199

RealScaler - image/video AI upscaler app (Real-ESRGAN)

Noise2noise Audio_denoising_without_clean_training_data ⭐ 52

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.

Deep Restore Pytorch ⭐ 40

Deep CNN for learning image restoration without clean data!

Python Sound Tool ⭐ 23

SoundPy (alpha stage) is a research-based python package for speech and sound. Applications include deep-learning, filtering, speech-enhancement, audio augmentation, feature extraction and visualization, dataset and audio file conversion, and beyond.

Awesome Speech Enhancement ⭐ 16

A curated list of awesome Speech Enhancement papers, libraries, datasets, and other resources.

Magic Mic ⭐ 15

Open Source Noise Cancellation App for Virtual Meetings

[Research] Monaural Speech Enhancement through Wave-U-Net (SEWUNet)

Openvino Real Time Noise Suppression Demo ⭐ 6

Modified version of OpenVINO noise_suppression_demo. This version can handle real-time audio stream from microphone and output to headphone.

Supernovasr ⭐ 6

Explore Super Image Resolution through sophisticated degradation modeling. Explore this approach to enhance real image quality and elevate your image enhancement capabilities

Multichannel Speech Enhancement With Deep Neural Networks ⭐ 5

This thesis applies an autoencoder deep neural network to the multichannel speech enhancement problem. It takes the problem from dataset generation to the model training

Integrated Hearing Aid App ⭐ 5

A smartphone applications with Convolutional Neural Network Voice Activity Detector, Adaptive Noise Reduction and Dynamic Audio Range Compression

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