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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 581–590 of 597 papers

TitleStatusHype
Compressive Sensing Approaches for Sparse Distribution Estimation Under Local Privacy—0
Compressive radio-interferometric sensing with random beamforming as rank-one signal covariance projections—0
Compressive Scanning Transmission Electron Microscopy—0
Compressive sensing adaptation for polynomial chaos expansions—0
Compressive Sensing and Morphology Singular Entropy-Based Real-time Secondary Voltage Control of Multi-area Power Systems—0
Compressive Sensing Approaches for Autonomous Object Detection in Video Sequences—0
Compressive Sensing Based Adaptive Active User Detection and Channel Estimation: Massive Access Meets Massive MIMO—0
Compressive Sensing Based Adaptive Defence Against Adversarial Images—0
Compressive sensing based privacy for fall detection—0
Compressive Sensing Based Sparse MIMO Array Optimization for Wideband Near-Field Imaging—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