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

Showing 581590 of 597 papers

TitleStatusHype
Deep Geometric Distillation Network for Compressive Sensing MRICode0
Learning to compress and search visual data in large-scale systemsCode0
Learning to Invert: Signal Recovery via Deep Convolutional NetworksCode0
Generative Patch Priors for Practical Compressive Image RecoveryCode0
Multi-Scale Deep Compressive Sensing NetworkCode0
Multi-Scale Deep Compressive Sensing NetworkCode0
Compressive Closeness in NetworksCode0
Operational Support Estimator NetworksCode0
Group-based Sparse Representation for Image RestorationCode0
Accurate Characterization of Non-Uniformly Sampled Time Series using Stochastic Differential EquationsCode0
Show:102550
← PrevPage 59 of 60Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DMP-DUN-Plus (4-step)Average PSNR42.82Unverified
2AMPA-NetAverage PSNR40.32Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR36.33Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR35.95Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR35.86Unverified