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 461–470 of 597 papers

TitleStatusHype
Data-Driven Forecast of Dengue Outbreaks in Brazil: A Critical Assessment of Climate Conditions for Different Capitals—0
A Data-Driven Compressive Sensing Framework Tailored For Energy-Efficient Wearable Sensing—0
CSVideoNet: A Real-time End-to-end Learning Framework for High-frame-rate Video Compressive SensingCode0
Design of Image Matched Non-Separable Wavelet using Convolutional Neural Network—0
Active Search for Sparse Signals with Region Sensing—0
Deep ADMM-Net for Compressive Sensing MRI—0
Fast recovery from a union of subspaces—0
Analyzing the group sparsity based on the rank minimization methods—0
Interpretable Recurrent Neural Networks Using Sequential Sparse RecoveryCode0
Detecting Breast Cancer using a Compressive Sensing Unmixing Algorithm—0
Show:102550
← PrevPage 47 of 60Next →
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