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 121–130 of 597 papers

TitleStatusHype
Compressive Sensing Approaches for Sparse Distribution Estimation Under Local Privacy—0
Compressive radio-interferometric sensing with random beamforming as rank-one signal covariance projections—0
Compressive Scanning Transmission Electron Microscopy—0
Compressive sensing adaptation for polynomial chaos expansions—0
Compressive Sensing and Morphology Singular Entropy-Based Real-time Secondary Voltage Control of Multi-area Power Systems—0
Compressive Sensing Approaches for Autonomous Object Detection in Video Sequences—0
Compressive Sensing Imaging of 3-D Object by a Holographic Algorithm—0
γ-Net: Superresolving SAR Tomographic Inversion via Deep Learning—0
Block-wise Lensless Compressive Camera—0
A Lightweight Human Pose Estimation Approach for Edge Computing-Enabled Metaverse with Compressive Sensing—0
Show:102550
← PrevPage 13 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