Noise Estimation
33 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Noise Estimation
Most implemented papers
Pyramid Real Image Denoising Network
Second, at the multi-scale denoising stage, pyramid pooling is utilized to extract multi-scale features.
Toward Convolutional Blind Denoising of Real Photographs
While deep convolutional neural networks (CNNs) have achieved impressive success in image denoising with additive white Gaussian noise (AWGN), their performance remains limited on real-world noisy photographs.
Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach
We present a theoretically grounded approach to train deep neural networks, including recurrent networks, subject to class-dependent label noise.
Learning with Confident Examples: Rank Pruning for Robust Classification with Noisy Labels
To highlight, RP with a CNN classifier can predict if an MNIST digit is a "one"or "not" with only 0. 25% error, and 0. 46 error across all digits, even when 50% of positive examples are mislabeled and 50% of observed positive labels are mislabeled negative examples.
Automatic, fast and robust characterization of noise distributions for diffusion MRI
Knowledge of the noise distribution in magnitude diffusion MRI images is the centerpiece to quantify uncertainties arising from the acquisition process.
Variational Denoising Network: Toward Blind Noise Modeling and Removal
zsyOAOA/VDNet
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NeurIPS 2019
On one hand, as other data-driven deep learning methods, our method, namely variational denoising network (VDN), can perform denoising efficiently due to its explicit form of posterior expression.
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.
