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 561–570 of 597 papers

TitleStatusHype
Finer Metagenomic Reconstruction via Biodiversity OptimizationCode0
Adaptive Measurement Network for CS Image ReconstructionCode0
Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and ThresholdsCode0
Flexible Intelligent Metasurface-Aided Wireless Communications: Architecture and PerformanceCode0
Online Learning Sensing Matrix and Sparsifying Dictionary Simultaneously for Compressive SensingCode0
Single-Pixel Compressive Imaging in Shift-Invariant Spaces via Exact Wavelet FramesCode0
A Compound Gaussian Least Squares Algorithm and Unrolled Network for Linear Inverse ProblemsCode0
Structure Preserving Compressive Sensing MRI Reconstruction using Generative Adversarial NetworksCode0
Multi-Channel Deep Networks for Block-Based Image Compressive SensingCode0
Digital Twin Aided Compressive Sensing: Enabling Site-Specific MIMO Hybrid PrecodingCode0
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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