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 251–275 of 597 papers

TitleStatusHype
Defect Detection by MIMO Wireless Sensing based on Weighted Low-Rank plus Sparse Recovery—0
Sampling and Reconstruction of Sparse Signals in Shift-Invariant Spaces: Generalized Shannon's Theorem Meets Compressive Sensing—0
Compressive Sensing and Neural Networks from a Statistical Learning Perspective—0
SUREMap: Predicting Uncertainty in CNN-based Image Reconstruction Using Stein's Unbiased Risk EstimateCode0
Compressive Sensing Based Situational Awareness and Sensor Placement for DC Microgrids with Relatively Fixed Operation Patterns—0
Model-based Decentralized Bayesian Algorithm for Distributed Compressed Sensing—0
Fast Uplink Grant-Free NOMA with Sinusoidal Spreading Sequences—0
Far-Field Minimum-Fuel Spacecraft Rendezvous using Koopman Operator and _2/_1 Optimization—0
Performance Indicator in Multilinear Compressive Learning—0
Automatic selection of basis-adaptive sparse polynomial chaos expansions for engineering applications—0
Regional Total Electron Content Map Generation based on Compressive Sensing—0
Compressive Phase Retrieval: Optimal Sample Complexity with Deep Generative Priors—0
Robust Mean Estimation in High Dimensions via _0 Minimization—0
One Bit to Rule Them All : Binarizing the Reconstruction in 1-bit Compressive Sensing—0
Optimal Data Detection and Signal Estimation in Systems with Input Noise—0
Jointly Sparse Signal Recovery and Support Recovery via Deep Learning with Applications in MIMO-based Grant-Free Random Access—0
Fast Nonconvex T_2^* Mapping Using ADMM—0
Third-Order Statistics Reconstruction from Compressive Measurements—0
mmRAPID: Machine Learning assisted Noncoherent Compressive Millimeter-Wave Beam AlignmentCode0
Across-domains transferability of Deep-RED in de-noising and compressive sensing recovery of seismic data—0
Deep Unfolding Basis Pursuit: Improving Sparse Channel Reconstruction via Data-Driven Measurement MatricesCode0
Crossterm-Free Time-Frequency Representation Exploiting Deep Convolutional Neural Network—0
Off-grid Multi-Source Passive Localization Using a Moving Array—0
Compressive dual-comb spectroscopy—0
Accurate Characterization of Non-Uniformly Sampled Time Series using Stochastic Differential EquationsCode0
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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