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 311–320 of 597 papers

TitleStatusHype
MsDC-DEQ-Net: Deep Equilibrium Model (DEQ) with Multi-scale Dilated Convolution for Image Compressive Sensing (CS)—0
Multichannel Compressive Sensing MRI Using Noiselet Encoding—0
Multilinear compressive sensing and an application to convolutional linear networks—0
Multipath Time-delay Estimation with Impulsive Noise via Bayesian Compressive Sensing—0
Multi-resolution Compressive Sensing Reconstruction—0
Multiscale Shrinkage and Lévy Processes—0
Multi-target Range and Angle detection for MIMO-FMCW radar with limited antennas—0
Multi-target Range, Doppler and Angle estimation in MIMO-FMCW Radar with Limited Measurements—0
Multi UAV-enabled Distributed Sensing: Cooperation Orchestration and Detection Protocol—0
Multi-view in Lensless Compressive Imaging—0
Show:102550
← PrevPage 32 of 60Next →
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