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 351–375 of 597 papers

TitleStatusHype
Optimization of retina-like illumination patterns in ghost imaging—0
Optimized Structured Sparse Sensing Matrices for Compressive Sensing—0
Optimizing Binary Symptom Checkers via Approximate Message Passing—0
PALMS: Parallel Adaptive Lasso with Multi-directional Signals for Latent Networks Reconstruction—0
Parameterless Optimal Approximate Message Passing—0
Performance Indicator in Multilinear Compressive Learning—0
Phase Retrieval using Untrained Neural Network Priors—0
Pinball Loss Minimization for One-bit Compressive Sensing: Convex Models and Algorithms—0
PIPO-Net: A Penalty-based Independent Parameters Optimization Deep Unfolding Network—0
PLUGIn-CS: A simple algorithm for compressive sensing with generative prior—0
Preconditioning for Accelerated Iteratively Reweighted Least Squares in Structured Sparsity Reconstruction—0
Primal-Dual Optimization Algorithms over Riemannian Manifolds: an Iteration Complexity Analysis—0
Prior Information-Aided ADMM for Multi-User Detection in Codebook-Based Grant-Free NOMA: Dynamic Scenarios—0
Privacy Preserving in Non-Intrusive Load Monitoring: A Differential Privacy Perspective—0
Provable Convergence of Plug-and-Play Priors with MMSE denoisers—0
Proximal Gradient-Based Unfolding for Massive Random Access in IoT Networks—0
Quantifying the influence of conformational uncertainty in biomolecular solvation—0
Quantity over Quality: Dithered Quantization for Compressive Radar Systems—0
RadioDUN: A Physics-Inspired Deep Unfolding Network for Radio Map Estimation—0
Rank-one matrix estimation: analysis of algorithmic and information theoretic limits by the spatial coupling method—0
Real-Time Object Detection and Localization in Compressive Sensed Video on Embedded Hardware—0
Reconstruction-Aware Imaging System Ranking by use of a Sparsity-Driven Numerical Observer Enabled by Variational Bayesian Inference—0
Reconstruction-free action inference from compressive imagers—0
Reconstruction-free Cascaded Adaptive Compressive Sensing—0
Reconstruction from Periodic Nonlinearities, With Applications to HDR Imaging—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