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 141–150 of 597 papers

TitleStatusHype
Compressive Sensing of ECG Signals using Plug-and-Play Regularization—0
Fast Disparity Estimation from a Single Compressed Light Field Measurement—0
Uformer-ICS: A U-Shaped Transformer for Image Compressive Sensing Service—0
Contact-Free Multi-Target Tracking Using Distributed Massive MIMO-OFDM Communication System: Prototype and Analysis—0
Joint Localization and Information Transfer for Reconfigurable Intelligent Surface Aided Full-Duplex Systems—0
Compressive Sensing Based Sparse MIMO Array Optimization for Wideband Near-Field Imaging—0
Unitary Approximate Message Passing for Matrix Factorization—0
Low-complexity Sparse Array Synthesis Based on Off-grid Compressive Sensing—0
Channel Estimation for Reconfigurable Intelligent Surface-Assisted Cell-Free Communications—0
Fast Compressive Channel Estimation for MmWave MIMO Hybrid Beamforming Systems—0
Show:102550
← PrevPage 15 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