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 101–125 of 597 papers

TitleStatusHype
ISAR imaging of space objects using encoded apertures—0
A Targeted Sampling Strategy for Compressive Cryo Focused Ion Beam Scanning Electron Microscopy—0
Downlink Massive MIMO Channel Estimation via Deep Unrolling : Sparsity Exploitations in Angular Domain—0
Compressed-Sensing-Based 3D Localization with Distributed Passive Reconfigurable Intelligent Surfaces—0
Comparison between Hadamard and canonical bases for in-situ wavefront correction and the effect of ordering in compressive sensing—0
Hybrid mmWave MIMO Systems under Hardware Impairments and Beam Squint: Channel Model and Dictionary Learning-aided Configuration—0
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
A Spatially Separable Attention Mechanism for massive MIMO CSI FeedbackCode1
Unitary Approximate Message Passing for Matrix Factorization—0
Channel Estimation for Reconfigurable Intelligent Surface-Assisted Cell-Free Communications—0
Fast Compressive Channel Estimation for MmWave MIMO Hybrid Beamforming Systems—0
Low-complexity Sparse Array Synthesis Based on Off-grid Compressive Sensing—0
D3C2-Net: Dual-Domain Deep Convolutional Coding Network for Compressive SensingCode1
ICRICS: Iterative Compensation Recovery for Image Compressive Sensing—0
Robust Deep Compressive Sensing with Recurrent-Residual Structural Constraints—0
Single-Pixel Image Reconstruction Based on Block Compressive Sensing and Deep Learning—0
Theoretical Perspectives on Deep Learning Methods in Inverse Problems—0
Hyperspectral image reconstruction for spectral camera based on ghost imaging via sparsity constraints using V-DUnet—0
Fast Low Rank column-wise Compressive Sensing for Accelerated Dynamic MRICode0
On Grid Compressive Sampling for Spherical Field Measurements in Acoustics—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