SOTAVerified

Compressive Sensing

Compressive Sensing is a new signal processing framework for efficiently acquiring and reconstructing a signal that have a sparse representation in a fixed linear basis.

Source: Sparse Estimation with Generalized Beta Mixture and the Horseshoe Prior

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 251–275 of 597 papers

TitleStatusHype
Feature-aware Label Space Dimension Reduction for Multi-label Classification—0
Compressive Sensing and Morphology Singular Entropy-Based Real-time Secondary Voltage Control of Multi-area Power Systems—0
Fingerprint Recognition under Missing Image Pixels Scenario—0
Fractal Compressive Sensing—0
A Gridless Compressive Sensing Based Channel Estimation for Millimeter Wave Massive MIMO Systems from 1-Bit Measurements—0
Adaptive and Cascaded Compressive Sensing—0
Compressive Sensing Imaging Using Caustic Lens Mask Generated by Periodic Perturbation in a Ripple Tank—0
Compressive Sensing Imaging of 3-D Object by a Holographic Algorithm—0
A Gridless Compressive Sensing Based Channel Estimation for Millimeter Wave MIMO OFDM Systems with One-Bit Quantization—0
DECONET: an Unfolding Network for Analysis-based Compressed Sensing with Generalization Error Bounds—0
Compressive Sensing and Neural Networks from a Statistical Learning Perspective—0
Compressive Sensing Empirical Wavelet Transform for Frequency-Banded Power Measurement Considering Interharmonics—0
Bayesian Compressive Sensing Using Normal Product Priors—0
Compressive-Sensing Data Reconstruction for Structural Health Monitoring: A Machine-Learning Approach—0
Active User Detection of Uplink Grant-Free SCMA in Frequency Selective Channel—0
A Compressive Sensing Approach for Federated Learning over Massive MIMO Communication Systems—0
Generalized Bregman Divergence and Gradient of Mutual Information for Vector Poisson Channels—0
Generalized Optimization of High Capacity Compressive Imaging Systems—0
From Group Sparse Coding to Rank Minimization: A Novel Denoising Model for Low-level Image Restoration—0
Generalized Tensor Summation Compressive Sensing Network (GTSNET): An Easy to Learn Compressive Sensing Operation—0
Generative adversarial network for super-resolution imaging through a fiber—0
Generative Adversarial Networks (GAN) Powered Fast Magnetic Resonance Imaging -- Mini Review, Comparison and Perspectives—0
Generative Inpainting Network Applications on Seismic Image Compression and Non-Uniform Sampling—0
Generative Models for Low-Dimensional Video Representation and Compressive Sensing—0
Gradient Estimation with Simultaneous Perturbation and Compressive Sensing—0
Show:102550
← PrevPage 11 of 24Next →
All datasetsSet11 cs=50%BSD68 CS=50%BSDS100 - 2x upscalingUrban100 - 2x upscaling

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DMP-DUN-Plus (4-step)Average PSNR42.82—Unverified
2AMPA-NetAverage PSNR40.32—Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR36.33—Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR35.95—Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR35.86—Unverified