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 176–200 of 597 papers

TitleStatusHype
A Compressive Sensing Video dataset using Pixel-wise coded exposure—0
A Bayesian Compressed Sensing Kalman Filter for Direction of Arrival Estimation—0
Comparison of threshold-based algorithms for sparse signal recovery—0
Comparison of Algorithms for Compressed Sensing of Magnetic Resonance Images—0
Analysis and Synthesis Denoisers for Forward-Backward Plug-and-Play Algorithms—0
Deep Random Projection Outlyingness for Unsupervised Anomaly Detection—0
Comparison between Hadamard and canonical bases for in-situ wavefront correction and the effect of ordering in compressive sensing—0
Deep Learning Techniques for Compressive Sensing-Based Reconstruction and Inference -- A Ubiquitous Systems Perspective—0
Comparative Study on Millimeter Wave Location-Based Beamforming—0
A data-driven approach to sampling matrix selection for compressive sensing—0
Communication-Efficient Decentralized Federated Learning via One-Bit Compressive Sensing—0
Deep Unfolding of Iteratively Reweighted ADMM for Wireless RF Sensing—0
Defect Detection by MIMO Wireless Sensing based on Weighted Low-Rank plus Sparse Recovery—0
Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging—0
Deep De-Aliasing for Fast Compressive Sensing MRI—0
Coded Aperture Radar Imaging Using Reconfigurable Intelligent Surfaces—0
Amplitude Retrieval for Channel Estimation of MIMO Systems with One-Bit ADCs—0
Designed Measurements for Vector Count Data—0
Design of Image Matched Non-Separable Wavelet using Convolutional Neural Network—0
DeepCodec: Adaptive Sensing and Recovery via Deep Convolutional Neural Networks—0
Dictionary-Learning-Based Reconstruction Method for Electron Tomography—0
Deep Attentive Wasserstein Generative Adversarial Networks for MRI Reconstruction with Recurrent Context-Awareness—0
Coarse-to-Fine Sparse Transformer for Hyperspectral Image Reconstruction—0
Adaptive Temporal Compressive Sensing for Video—0
A Compressive Sensing Based Method for Harmonic State Estimation—0
Show:102550
← PrevPage 8 of 24Next →
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