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

Showing 401450 of 597 papers

TitleStatusHype
Sampling-Priors-Augmented Deep Unfolding Network for Robust Video Compressive Sensing0
Scalable Deep Compressive Sensing0
Secure Directional Modulation with Movable Antenna Array Aided by RIS0
Selective Sensing: A Data-driven Nonuniform Subsampling Approach for Computation-free On-Sensor Data Dimensionality Reduction0
Separation of undersampled composite signals using the Dantzig selector with overcomplete dictionaries0
Signal processing after quadratic random sketching with optical units0
Signal processing with optical quadratic random sketches0
Signal Reconstruction Framework Based On Projections Onto Epigraph Set Of A Convex Cost Function (PESC)0
Signal Recovery with Non-Expansive Generative Network Priors0
Signal to Noise Ratio in Lensless Compressive Imaging0
Simultaneously sparse and low-rank abundance matrix estimation for hyperspectral image unmixing0
Single-Pixel Image Reconstruction Based on Block Compressive Sensing and Deep Learning0
Single pixel imaging at high pixel resolutions0
Site-specific online compressive beam codebook learning in mmWave vehicular communication0
Sketching for Large-Scale Learning of Mixture Models0
SnapCap: Efficient Snapshot Compressive Video Captioning0
Snapshot fiber spectral imaging using speckle correlations and compressive sensing0
Source Localization and Tracking for Dynamic Radio Cartography using Directional Antennas0
SpaRCS: Recovering low-rank and sparse matrices from compressive measurements0
Sparse Estimation with Generalized Beta Mixture and the Horseshoe Prior0
Sparse Estimation with Structured Dictionaries0
Sparse Models for Machine Learning0
CMAR-Net: Accurate Cross-Modal 3D SAR Reconstruction of Vehicle Targets with Sparse-Aspect Multi-Baseline Data0
Automatic selection of basis-adaptive sparse polynomial chaos expansions for engineering applications0
Sparse Polynomial Chaos expansions using Variational Relevance Vector Machines0
Sparse Reconstruction of Compressive Sensing MRI using Cross-Domain Stochastically Fully Connected Conditional Random Fields0
Sparse Signal Processing for Massive Connectivity via Mixed-Integer Programming0
Sparse Signal Reconstruction with Multiple Side Information using Adaptive Weights for Multiview Sources0
Sparse Signal Recovery Using Markov Random Fields0
Sparsity-Based Channel Estimation Exploiting Deep Unrolling for Downlink Massive MIMO0
Spatial Channel Covariance Estimation for Hybrid Architectures Based on Tensor Decompositions0
Spatially Directional Predictive Coding for Block-based Compressive Sensing of Natural Images0
Spectrum from Defocus: Fast Spectral Imaging with Chromatic Focal Stack0
Speeding-Up Convergence via Sequential Subspace Optimization: Current State and Future Directions0
Memory-efficient model-based deep learning with convergence and robustness guarantees0
Stable and robust sampling strategies for compressive imaging0
STAR-RIS-Enabled Simultaneous Indoor and Outdoor 3D Localization: Theoretical Analysis and Algorithmic Design0
Stochastic Deep Compressive Sensing for the Reconstruction of Diffusion Tensor Cardiac MRI0
Stochastic Solutions for Linear Inverse Problems using the Prior Implicit in a Denoiser0
Structural Group Sparse Representation for Image Compressive Sensing Recovery0
Structurally Adaptive Multi-Derivative Regularization for Image Recovery from Sparse Fourier Samples0
Structured Sparsity: Discrete and Convex approaches0
Study of the gOMP Algorithm for Recovery of Compressed Sensed Hyperspectral Images0
Study on Compressed Sensing of Action Potential0
Sub-Pixel Registration of Wavelet-Encoded Images0
Subspace Constrained Variational Bayesian Inference for Structured Compressive Sensing with a Dynamic Grid0
Super-Resolution of Brain MRI Images using Overcomplete Dictionaries and Nonlocal Similarity0
Theoretical Perspectives on Deep Learning Methods in Inverse Problems0
The Power of Triply Complementary Priors for Image Compressive Sensing0
The Role of Interactivity in Structured Estimation0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DMP-DUN-Plus (4-step)Average PSNR42.82Unverified
2AMPA-NetAverage PSNR40.32Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR36.33Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR35.95Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR35.86Unverified