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 191–200 of 597 papers

TitleStatusHype
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