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 51–75 of 597 papers

TitleStatusHype
1-Bit Compressive Sensing for Efficient Federated Learning Over the Air—0
A Deep Learning Approach to Structured Signal Recovery—0
An Off-grid Compressive Sensing Strategy for the Subarray Synthesis of Non-uniform Linear Arrays—0
A Bayesian Lasso based Sparse Learning Model—0
A Nonlinear Weighted Total Variation Image Reconstruction Algorithm for Electrical Capacitance Tomography—0
A Novel Radar Constant False Alarm Rate Detection Algorithm Based on VAMP Deep Unfolding—0
A Parallel Compressive Imaging Architecture for One-Shot Acquisition—0
C^2SP-Net: Joint Compression and Classification Network for Epilepsy Seizure Prediction—0
A Survey: Non-Orthogonal Multiple Access with Compressed Sensing Multiuser Detection for mMTC—0
Asynchronous Multi Agent Active Search—0
A Targeted Sampling Strategy for Compressive Cryo Focused Ion Beam Scanning Electron Microscopy—0
A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI—0
A Data-Driven Compressive Sensing Framework Tailored For Energy-Efficient Wearable Sensing—0
Analyzing the group sparsity based on the rank minimization methods—0
A Compressive Sensing Video dataset using Pixel-wise coded exposure—0
CAIM: Cooperative Angle of Arrival Estimation using the Ising Method—0
Capture and Recovery of Connected Vehicle Data: A Compressive Sensing Approach—0
Channel Estimation for Hybrid RIS Aided MIMO Communications via Atomic Norm Minimization—0
Analysis and Synthesis Denoisers for Forward-Backward Plug-and-Play Algorithms—0
A data-driven approach to sampling matrix selection for compressive sensing—0
Amplitude Retrieval for Channel Estimation of MIMO Systems with One-Bit ADCs—0
Adaptive Temporal Compressive Sensing for Video—0
A Compressive Sensing Based Method for Harmonic State Estimation—0
A Model-data-driven Network Embedding Multidimensional Features for Tomographic SAR Imaging—0
Ambient Occlusion via Compressive Visibility Estimation—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