Results 71 to 80 of about 272,612 (359)
Boosting of Image Denoising Algorithms
, 2015 In this paper we propose a generic recursive algorithm for improving image denoising methods. Given the initial denoised image, we suggest repeating the following "SOS" procedure: (i) (S)trengthen the signal by adding the previous denoised image to the ...
Elad, Michael, Romano, Yaniv
core +1 more source
Sparse Representing Denoising of Hyperspectral Data for Water Color Remote Sensing
Applied Sciences, 2022 Hyperspectral data are important for water color remote sensing. The inevitable noise will devalue its application. In this study, we developed a 1-D denoising method for water hyperspectral data, based on sparse representing.
Yulong Guo +7 more
doaj +1 more source
3D Point Cloud Denoising via Deep Neural Network based Local Surface Estimation
, 2019 We present a neural-network-based architecture for 3D point cloud denoising called neural projection denoising (NPD). In our previous work, we proposed a two-stage denoising algorithm, which first estimates reference planes and follows by projecting ...
Chen, Siheng +2 more
core +1 more source
On the energy leakage of discrete wavelet transform [PDF]
, 2008 The energy leakage is an inherent deficiency of discrete wavelet transform (DWT) which is often ignored by researchers and practitioners. In this paper, a systematic investigation into the energy leakage is reported.
Abry +27 more
core +1 more source
From denoising diffusions to denoising Markov models
Journal of the Royal Statistical Society Series B: Statistical MethodologyAbstract Denoising diffusions are state-of-the-art generative models exhibiting remarkable empirical performance. They work by diffusing the data distribution into a Gaussian distribution and then learning to reverse this noising process to obtain synthetic datapoints.
Joe Benton +4 more
openaire +3 more sources
No-reference Image Denoising Quality Assessment [PDF]
, 2018 A wide variety of image denoising methods are available now. However, the performance of a denoising algorithm often depends on individual input noisy images as well as its parameter setting.
Lu, Si
core +2 more sources
Molecular Oncology, EarlyView.Clinical trials on PARP inhibitors in urothelial carcinoma (UC) showed limited efficacy and a lack of predictive biomarkers. We propose SLFN5, SLFN11, and OAS1 as UC‐specific response predictors. We suggest Talazoparib as the better PARP inhibitor for UC than Olaparib.
Jutta Schmitz +15 more
wiley +1 more source
Overview of Research on Digital Image Denoising Methods
SensorsDuring image collection, images are often polluted by noise because of imaging conditions and equipment limitations. Images are also disturbed by external noise during compression and transmission, which adversely affects consequent processing, like ...
Jing Mao +3 more
doaj +1 more source
, 2010 A denoising technique based on noise invalidation is proposed. The adaptive approach derives a noise signature from the noise order statistics and utilizes the signature to denoise the data. The novelty of this approach is in presenting a general-purpose
Beheshti, Soosan +3 more
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Relapsing–Remitting Multiple Sclerosis Is Associated With a Dysbiotic Oral Microbiome
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Multiple sclerosis (MS) is a chronic autoimmune disorder characterized by inflammation, demyelination, and neurological impairment. While the gut microbiota's role in MS is extensively studied, the association between the oral microbiota and MS remains underexplored, particularly in North American cohorts.
Sukirth M. Ganesan +12 more
wiley +1 more source