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 476–500 of 597 papers

TitleStatusHype
What Happens on the Edge, Stays on the Edge: Toward Compressive Deep Learning—0
1-Bit Compressive Sensing for Efficient Federated Learning Over the Air—0
Zero-Shot Solving of Imaging Inverse Problems via Noise-Refined Likelihood Guided Diffusion Models—0
A Probabilistic Bayesian Approach to Recover R_2^* map and Phase Images for Quantitative Susceptibility Mapping—0
A Bayesian Compressed Sensing Kalman Filter for Direction of Arrival Estimation—0
A Block Sparsity Based Estimator for mmWave Massive MIMO Channels with Beam Squint—0
Accelerated parallel MRI using memory efficient and robust monotone operator learning (MOL)—0
A Comparative Study of Compressive Sensing Algorithms for Hyperspectral Imaging Reconstruction—0
A Comparison of Clustering and Missing Data Methods for Health Sciences—0
A Compressive Sensing Approach to Community Detection with Applications—0
A Compressive Sensing Based Method for Harmonic State Estimation—0
A Compressive Sensing Video dataset using Pixel-wise coded exposure—0
Across-domains transferability of Deep-RED in de-noising and compressive sensing recovery of seismic data—0
Active Search for Sparse Signals with Region Sensing—0
Active User Detection of Uplink Grant-Free SCMA in Frequency Selective Channel—0
Adaptive and Cascaded Compressive Sensing—0
Adaptive foveated single-pixel imaging with dynamic super-sampling—0
Adaptive low rank and sparse decomposition of video using compressive sensing—0
Adaptive-Rate Compressive Sensing Using Side Information—0
Adaptive Temporal Compressive Sensing for Video—0
A data-driven approach to sampling matrix selection for compressive sensing—0
A Data-Driven Compressive Sensing Framework Tailored For Energy-Efficient Wearable Sensing—0
A Deep Learning Approach to Structured Signal Recovery—0
ADMM-Net: A Deep Learning Approach for Compressive Sensing MRI—0
A Fast Algorithm for Low Rank + Sparse column-wise Compressive Sensing—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