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 1–25 of 597 papers

TitleStatusHype
Disentangling coincident cell events using deep transfer learning and compressive sensing—0
Zero-Shot Solving of Imaging Inverse Problems via Noise-Refined Likelihood Guided Diffusion Models—0
RadioDUN: A Physics-Inspired Deep Unfolding Network for Radio Map Estimation—0
Low-Complexity Super-Resolution Signature Estimation of XL-MIMO FMCW Radar—0
Discrete and Continuous Difference of Submodular MinimizationCode0
Training Beam Design for Channel Estimation in Hybrid mmWave MIMO Systems—0
Knockoff-Guided Compressive Sensing: A Statistical Machine Learning Framework for Support-Assured Signal RecoveryCode0
AltGDmin: Alternating GD and Minimization for Partly-Decoupled (Federated) Optimization—0
A Novel Radar Constant False Alarm Rate Detection Algorithm Based on VAMP Deep Unfolding—0
Secure Directional Modulation with Movable Antenna Array Aided by RIS—0
Spectrum from Defocus: Fast Spectral Imaging with Chromatic Focal Stack—0
Sampling Innovation-Based Adaptive Compressive SensingCode1
Modeling and Optimization for Flexible Cylindrical Arrays-Enabled Wireless CommunicationsCode0
Flexible Intelligent Metasurface-Aided Wireless Communications: Architecture and PerformanceCode0
Using Powerful Prior Knowledge of Diffusion Model in Deep Unfolding Networks for Image Compressive SensingCode1
Group Sparsity Methods for Compressive Space-Frequency Channel Estimation and Spatial Equalization in Fluid Antenna System—0
Compressive Sensing Empirical Wavelet Transform for Frequency-Banded Power Measurement Considering Interharmonics—0
Channel Estimation for RIS-Aided MU-MIMO mmWave Systems with Practical Hybrid Architecture—0
Multi-target Range, Doppler and Angle estimation in MIMO-FMCW Radar with Limited Measurements—0
HUNet: Homotopy Unfolding Network for Image Compressive SensingCode0
Exploiting Dynamic Sparsity for Near-Field Spatial Non-Stationary XL-MIMO Channel Tracking—0
Analysis and Synthesis Denoisers for Forward-Backward Plug-and-Play Algorithms—0
PALMS: Parallel Adaptive Lasso with Multi-directional Signals for Latent Networks Reconstruction—0
Block based Adaptive Compressive Sensing with Sampling Rate Control—0
Sparse Bayesian Generative Modeling for Compressive SensingCode0
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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