SOTAVerified

Denoising

Denoising is a task in image processing and computer vision that aims to remove or reduce noise from an image. Noise can be introduced into an image due to various reasons, such as camera sensor limitations, lighting conditions, and compression artifacts. The goal of denoising is to recover the original image, which is considered to be noise-free, from a noisy observation.

( Image credit: Beyond a Gaussian Denoiser )

Papers

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Showing 5251–5275 of 7282 papers

TitleStatusHype
A novel approach for automatic acoustic novelty detection using a denoising autoencoder with bidirectional LSTM neural networks—0
A novel convolutional neural network model to remove muscle artifacts from EEG—0
A Novel Denoising Technique and Deep Learning Based Hybrid Wind Speed Forecasting Model for Variable Terrain Conditions—0
A novel diffusion recommendation algorithm based on multi-scale cnn and residual lstm—0
A Novel ECG Denoising Scheme Using the Ensemble Kalman Filter—0
A novel ECG signal denoising filter selection algorithm based on conventional neural networks—0
A Novel Image Denoising Algorithm Using Concepts of Quantum Many-Body Theory—0
A Novel Score-CAM based Denoiser for Spectrographic Signature Extraction without Ground Truth—0
A Novel U-Net Architecture for Denoising of Real-world Noise Corrupted Phonocardiogram Signal—0
An overview of diffusion models for generative artificial intelligence—0
An Overview of Distant Supervision for Relation Extraction with a Focus on Denoising and Pre-training Methods—0
Anti-Bandit Neural Architecture Search for Model Defense—0
Anti-Inpainting: A Proactive Defense against Malicious Diffusion-based Inpainters under Unknown Conditions—0
Signal Processing for Implicit Neural Representations—0
Signal Processing on Higher-Order Networks: Livin' on the Edge ... and Beyond—0
An unsupervised deep learning framework for medical image denoising—0
AnyEnhance: A Unified Generative Model with Prompt-Guidance and Self-Critic for Voice Enhancement—0
AnyLogo: Symbiotic Subject-Driven Diffusion System with Gemini Status—0
A New Perspective On Denoising Based On Optimal Transport—0
Image Denoising Using the Geodesics' Gramian of the Manifold Underlying Patch-Space—0
Signal processing on simplicial complexes—0
A Permutation-based Model for Crowd Labeling: Optimal Estimation and Robustness—0
Signal Quality Auditing for Time-series Data—0
A Pipeline for Lenslet Light Field Quality Enhancement—0
Signal Reconstruction Framework Based On Projections Onto Epigraph Set Of A Convex Cost Function (PESC)—0
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All datasetsDarmstadt Noise DatasetDIV2KDNDiris

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81—Unverified
2Pixel-shuffling DownsamplingPSNR38.4—Unverified
3TWSCPSNR37.93—Unverified
4CBDNet(Syn)PSNR37.57—Unverified
5MCWNNMPSNR37.38—Unverified
6Han et alPSNR35.95—Unverified
7FFDNetPSNR34.4—Unverified
8TNRDPSNR33.65—Unverified
9CDnCNN-BPSNR32.43—Unverified
10NLRNPSNR30.8—Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92—Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64—Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61—Unverified