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 151–175 of 597 papers

TitleStatusHype
ICRICS: Iterative Compensation Recovery for Image Compressive Sensing—0
Robust Deep Compressive Sensing with Recurrent-Residual Structural Constraints—0
Single-Pixel Image Reconstruction Based on Block Compressive Sensing and Deep Learning—0
Theoretical Perspectives on Deep Learning Methods in Inverse Problems—0
Hyperspectral image reconstruction for spectral camera based on ghost imaging via sparsity constraints using V-DUnet—0
Fast Low Rank column-wise Compressive Sensing for Accelerated Dynamic MRICode0
On Grid Compressive Sampling for Spherical Field Measurements in Acoustics—0
A Fast Alternating Minimization Algorithm for Coded Aperture Snapshot Spectral Imaging Based on Sparsity and Deep Image Priors—0
Compressive Sensing with Wigner D-functions on Subsets of the Sphere—0
Single pixel imaging at high pixel resolutions—0
Machine Learning Prediction for Phase-less Millimeter-Wave Beam Tracking—0
Memory-efficient model-based deep learning with convergence and robustness guarantees—0
Compressive Fourier collocation methods for high-dimensional diffusion equations with periodic boundary conditions—0
Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive ImagingCode0
Evaluation of the Effects of Compressive Spectrum Sensing Parameters on Primary User Behavior Estimation—0
Nonconvex L_ 1/2 -Regularized Nonlocal Self-similarity Denoiser for Compressive Sensing based CT Reconstruction—0
DECONET: an Unfolding Network for Analysis-based Compressed Sensing with Generalization Error Bounds—0
Signal Recovery with Non-Expansive Generative Network Priors—0
Blind Orthogonal Least Squares based Compressive Spectrum Sensing—0
A General Compressive Sensing Construct using Density Evolution—0
Adaptive and Cascaded Compressive Sensing—0
The Role of Interactivity in Structured Estimation—0
One-Bit Compressive Sensing: Can We Go Deep and Blind?—0
Coarse-to-Fine Sparse Transformer for Hyperspectral Image ReconstructionCode0
_1DecNet+: A new architecture framework by _1 decomposition and iteration unfolding for sparse feature segmentation—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