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

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Showing 151–200 of 597 papers

TitleStatusHype
Composing Normalizing Flows for Inverse Problems—0
CONGO: Compressive Online Gradient Optimization—0
Contact-Free Multi-Target Tracking Using Distributed Massive MIMO-OFDM Communication System: Prototype and Analysis—0
ConvCSNet: A Convolutional Compressive Sensing Framework Based on Deep Learning—0
Convex Reconstruction of Structured Matrix Signals from Linear Measurements (I): Theoretical Results—0
Convolutional Neural Networks for Non-iterative Reconstruction of Compressively Sensed Images—0
Convolutional sparse coding for capturing high speed video content—0
Convolutional Sparse Support Estimator Network (CSEN) From energy efficient support estimation to learning-aided Compressive Sensing—0
A Probabilistic Bayesian Approach to Recover R_2^* map and Phase Images for Quantitative Susceptibility Mapping—0
Co-VeGAN: Complex-Valued Generative Adversarial Network for Compressive Sensing MR Image Reconstruction—0
Compressive Sensing via Low-Rank Gaussian Mixture Models—0
CPRL -- An Extension of Compressive Sensing to the Phase Retrieval Problem—0
Compressive Sensing via Convolutional Factor Analysis—0
Crossterm-Free Time-Frequency Representation Exploiting Deep Convolutional Neural Network—0
Binary Linear Classification and Feature Selection via Generalized Approximate Message Passing—0
CSMCNet: Scalable Video Compressive Sensing Reconstruction with Interpretable Motion Estimation—0
Channel Estimation for Reconfigurable Intelligent Surface-Assisted Cell-Free Communications—0
CSWA: Aggregation-Free Spatial-Temporal Community Sensing—0
Compressive Sensing: Performance Comparison Of Sparse Recovery Algorithms—0
DAEs for Linear Inverse Problems: Improved Recovery with Provable Guarantees—0
Data-Driven Deep Learning to Design Pilot and Channel Estimator For Massive MIMO—0
Data-Driven Forecast of Dengue Outbreaks in Brazil: A Critical Assessment of Climate Conditions for Different Capitals—0
Compressive Sensing Based Situational Awareness and Sensor Placement for DC Microgrids with Relatively Fixed Operation Patterns—0
Deep ADMM-Net for Compressive Sensing MRI—0
Compressive Sensing of Sparse Tensors—0
Deep Attentive Wasserstein Generative Adversarial Networks for MRI Reconstruction with Recurrent Context-Awareness—0
Binary Fused Compressive Sensing: 1-Bit Compressive Sensing meets Group Sparsity—0
A Hybrid Architecture for On-Device Compressive Machine Learning—0
Deep De-Aliasing for Fast Compressive Sensing MRI—0
Coded Aperture Radar Imaging Using Reconfigurable Intelligent Surfaces—0
Compressive Sensing of Signals from a GMM with Sparse Precision Matrices—0
Communication-Efficient Decentralized Federated Learning via One-Bit Compressive Sensing—0
Compressive Sensing of ECG Signals using Plug-and-Play Regularization—0
Binary Compressive Sensing via Smoothed _0 Gradient Descent—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 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
Compressive Sensing of Color Images Using Nonlocal Higher Order Dictionary—0
Compressed-Domain Detection and Estimation for Colocated MIMO Radar—0
Depth and Transient Imaging With Compressive SPAD Array Cameras—0
Designed Measurements for Vector Count Data—0
Design of Image Matched Non-Separable Wavelet using Convolutional Neural Network—0
Detecting Breast Cancer using a Compressive Sensing Unmixing Algorithm—0
Dictionary-Learning-Based Reconstruction Method for Electron Tomography—0
Compressed-Sensing-Based 3D Localization with Distributed Passive Reconfigurable Intelligent Surfaces—0
A Data-Driven Compressive Sensing Framework Tailored For Energy-Efficient Wearable Sensing—0
On the Fourier transform of a quantitative trait: Implications for compressive sensing—0
Compressive Sensing MRI with Wavelet Tree Sparsity—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