Noise Estimation
43 papers with code • 1 benchmarks • 1 datasets
Libraries
Use these libraries to find Noise Estimation models and implementations
SIDD
Most implemented papers
RENOIR - A Dataset for Real Low-Light Image Noise Reduction
Aftaab99/DenoisingAutoencoder
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Image denoising algorithms are evaluated using images corrupted by artificial noise, which may lead to incorrect conclusions about their performances on real noise.
A Convolutional Neural Network Smartphone App for Real-Time Voice Activity Detection
This paper presents a smartphone app that performs real-time voice activity detection based on convolutional neural network.
Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy Labels
uds-lsv/noise-matrix-ner
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IJCNLP 2019
In low-resource settings, the performance of supervised labeling models can be improved with automatically annotated or distantly supervised data, which is cheap to create but often noisy.
Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning
elad-amrani/ssml
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One of the key factors of enabling machine learning models to comprehend and solve real-world tasks is to leverage multimodal data.
Learning Camera-Aware Noise Models
arcchang1236/CA-NoiseGAN
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ECCV 2020
Modeling imaging sensor noise is a fundamental problem for image processing and computer vision applications.
DNN-based mask estimation for distributed speech enhancement in spatially unconstrained microphone arrays
nfurnon/disco
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Deep neural network (DNN)-based speech enhancement algorithms in microphone arrays have now proven to be efficient solutions to speech understanding and speech recognition in noisy environments.
Self-Supervised Image Prior Learning With GMM From a Single Noisy Image
It can simultaneously achieve the noise level estimation and the image prior learning directly from only a single noisy image.
Joint self-supervised blind denoising and noise estimation
IVRL/w2s
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Assuming that the noisy observations are independent conditionally to the signal, the networks can be jointly trained without clean training data.
The Fragility of Noise Estimation in Kalman Filter: Optimization Can Handle Model-Misspecification
ido90/UsingKalmanFilterTheRightWay
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The Kalman Filter (KF) parameters are traditionally determined by noise estimation, since under the KF assumptions, the state prediction errors are minimized when the parameters correspond to the noise covariance.
Noise-based cyberattacks generating fake P300 waves in brain–computer interfaces
This work presents and analyzes the impact of four noise-based cyberattacks attempting to generate fake P300 waves in two different phases of a BCI framework.
