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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

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Showing 151–200 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
HDNet: High-resolution Dual-domain Learning for Spectral Compressive ImagingCode0
Motion-aware Dynamic Graph Neural Network for Video Compressive Sensing—0
Mathematical Foundation of Sparsity-based Multi-snapshot Spectral Estimation—0
Monotonically Convergent Regularization by Denoising—0
Image-to-Image MLP-mixer for Image ReconstructionCode0
Unsupervised Sparse Unmixing of Atmospheric Trace Gases from Hyperspectral Satellite Data—0
Low dosage 3D volume fluorescence microscopy imaging using compressive sensing—0
Generative adversarial network for super-resolution imaging through a fiber—0
HLRTF: Hierarchical Low-Rank Tensor Factorization for Inverse Problems in Multi-Dimensional Imaging—0
An Off-grid Compressive Sensing Strategy for the Subarray Synthesis of Non-uniform Linear Arrays—0
Compressive Scanning Transmission Electron Microscopy—0
More is Less: Inducing Sparsity via Overparameterization—0
γ-Net: Superresolving SAR Tomographic Inversion via Deep Learning—0
Differentiable Gaussianization Layers for Inverse Problems Regularized by Deep Generative ModelsCode0
Stochastic Solutions for Linear Inverse Problems using the Prior Implicit in a Denoiser—0
Moment Transform-Based Compressive Sensing in Image Processing—0
Optimizing Binary Symptom Checkers via Approximate Message Passing—0
C^2SP-Net: Joint Compression and Classification Network for Epilepsy Seizure Prediction—0
Robust lEarned Shrinkage-Thresholding (REST): Robust unrolling for sparse recover—0
PLUGIn-CS: A simple algorithm for compressive sensing with generative prior—0
Learning a Compressive Sensing Matrix with Structural Constraints via Maximum Mean Discrepancy Optimization—0
Revisit Dictionary Learning for Video Compressive Sensing under the Plug-and-Play Framework—0
Compressive Sensing Based Adaptive Defence Against Adversarial Images—0
Fast Scalable Image Restoration using Total Variation Priors and Expectation Propagation—0
Lottery Image Prior—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