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

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Showing 541–550 of 597 papers

TitleStatusHype
Block-wise Lensless Compressive Camera—0
γ-Net: Superresolving SAR Tomographic Inversion via Deep Learning—0
C^2SP-Net: Joint Compression and Classification Network for Epilepsy Seizure Prediction—0
CAIM: Cooperative Angle of Arrival Estimation using the Ising Method—0
Capture and Recovery of Connected Vehicle Data: A Compressive Sensing Approach—0
Channel Estimation for Hybrid RIS Aided MIMO Communications via Atomic Norm Minimization—0
Channel Estimation for Reconfigurable Intelligent Surface-Assisted Cell-Free Communications—0
Channel Estimation for Reconfigurable Intelligent Surface Aided Multi-User mmWave MIMO Systems—0
Channel Estimation for RIS-Aided MU-MIMO mmWave Systems with Practical Hybrid Architecture—0
Coarse-to-Fine Sparse Transformer for Hyperspectral Image Reconstruction—0
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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