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 371–380 of 597 papers

TitleStatusHype
Quantity over Quality: Dithered Quantization for Compressive Radar Systems—0
High SNR Consistent Compressive Sensing Without Signal and Noise Statistics—0
Capture and Recovery of Connected Vehicle Data: A Compressive Sensing Approach—0
Compressive Sensing and Morphology Singular Entropy-Based Real-time Secondary Voltage Control of Multi-area Power Systems—0
A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI—0
Forensic Discrimination between Traditional and Compressive Imaging Systems—0
Non-Local Compressive Sensing Based SAR Tomography—0
Compressive Single-pixel Fourier Transform Imaging using Structured Illumination—0
Snapshot fiber spectral imaging using speckle correlations and compressive sensing—0
Compressively Sensed Image Recognition—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