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Classification with Asymmetric Label Noise: Consistency and Maximal Denoising
Classification Asymmetric Label Noise Consistency Maximal Denoising
2013/4/27
In many real-world classification problems, the labels of training examples are randomly corrupted. Previous theoretical work on classification with label noise assumes that the two classes are separa...
Denoising Deep Neural Networks Based Voice Activity Detection
Deep learning denoising deep neural net-works voice activity detection
2013/4/28
Recently, the deep-belief-networks (DBN) based voice activity detection (VAD) has been proposed. It is powerful in fusing the advantages of multiple features, and achieves the state-of-the-art perform...
A two-stage denoising filter: the preprocessed Yaroslavsky filter
Image denoising Yaroslavsky lter Wavelets Curvelets Nonlocal Means
2012/9/18
This paper describes a simple image noise removal method which combines a preprocessing step with the Yaroslavsky lter for strong numerical, visual, and theoretical performance on a broad class of im...
Locally adaptive image denoising by a statistical multiresolution criterion
Image reconstruction statistical multiresolution crite-rion bandwidth selection
2010/3/9
We demonstrate how one can choose the smoothing parameter in
image denoising by a statistical multiresolution criterion, both globally
and locally. Using inhomogeneous di usion and total variation r...
Nonparametric denoising Signals of Unknown Local Structure，II：Nonparametric Regression Estimation
Nonparametric denoising adaptive filtering minimax estimation nonparametric regression
2010/3/18
We consider the problem of recovering of continuous multi-dimensional functions f
from the noisy observations over the regular grid m−1Zd, m ∈ N∗. Our focus is at
the adaptive estimation...