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 251–275 of 597 papers

TitleStatusHype
Feature-aware Label Space Dimension Reduction for Multi-label Classification—0
CSWA: Aggregation-Free Spatial-Temporal Community Sensing—0
Fingerprint Recognition under Missing Image Pixels Scenario—0
Fractal Compressive Sensing—0
Channel Estimation for Reconfigurable Intelligent Surface-Assisted Cell-Free Communications—0
Ambient Occlusion via Compressive Visibility Estimation—0
Adaptive-Rate Compressive Sensing Using Side Information—0
CSMCNet: Scalable Video Compressive Sensing Reconstruction with Interpretable Motion Estimation—0
Channel Estimation for Hybrid RIS Aided MIMO Communications via Atomic Norm Minimization—0
Crossterm-Free Time-Frequency Representation Exploiting Deep Convolutional Neural Network—0
Capture and Recovery of Connected Vehicle Data: A Compressive Sensing Approach—0
CPRL -- An Extension of Compressive Sensing to the Phase Retrieval Problem—0
CAIM: Cooperative Angle of Arrival Estimation using the Ising Method—0
Co-VeGAN: Complex-Valued Generative Adversarial Network for Compressive Sensing MR Image Reconstruction—0
C^2SP-Net: Joint Compression and Classification Network for Epilepsy Seizure Prediction—0
AltGDmin: Alternating GD and Minimization for Partly-Decoupled (Federated) Optimization—0
A Compressive Sensing Approach to Community Detection with Applications—0
Accelerated parallel MRI using memory efficient and robust monotone operator learning (MOL)—0
Convolutional Sparse Support Estimator Network (CSEN) From energy efficient support estimation to learning-aided Compressive Sensing—0
Convolutional sparse coding for capturing high speed video content—0
γ-Net: Superresolving SAR Tomographic Inversion via Deep Learning—0
Convolutional Neural Networks for Non-iterative Reconstruction of Compressively Sensed Images—0
Convex Reconstruction of Structured Matrix Signals from Linear Measurements (I): Theoretical Results—0
Block-wise Lensless Compressive Camera—0
A Lightweight Human Pose Estimation Approach for Edge Computing-Enabled Metaverse with 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