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

Showing 551575 of 597 papers

TitleStatusHype
Coded Aperture Radar Imaging Using Reconfigurable Intelligent Surfaces0
Communication-Efficient Decentralized Federated Learning via One-Bit Compressive Sensing0
Comparative Study on Millimeter Wave Location-Based Beamforming0
Comparison between Hadamard and canonical bases for in-situ wavefront correction and the effect of ordering in compressive sensing0
Comparison of Algorithms for Compressed Sensing of Magnetic Resonance Images0
Comparison of threshold-based algorithms for sparse signal recovery0
Compressed-Domain Detection and Estimation for Colocated MIMO Radar0
Compressed Domain Image Classification Using a Dynamic-Rate Neural Network0
Compressed domain vibration detection and classification for distributed acoustic sensing0
Compressed-Sensing-Based 3D Localization with Distributed Passive Reconfigurable Intelligent Surfaces0
Compressed sensing MRI using masked DCT and DFT measurements0
Compressed Sensing SAR Imaging with Multilook Processing0
Compression Boosts Differentially Private Federated Learning0
Compression Ratio Learning and Semantic Communications for Video Imaging0
Compression, Restoration, Re-sampling, Compressive Sensing: Fast Transforms in Digital Imaging0
Compressive Acquisition of Dynamic Scenes0
Compressive adaptive computational ghost imaging0
Compressive dual-comb spectroscopy0
Compressive Fourier collocation methods for high-dimensional diffusion equations with periodic boundary conditions0
Compressive Hyperspectral Imaging: Fourier Transform Interferometry meets Single Pixel Camera0
Compressive hyperspectral imaging via adaptive sampling and dictionary learning0
Compressive Hyperspectral Imaging with Side Information0
Compressive lensless endoscopy with partial speckle scanning0
Compressive Light Field Reconstructions using Deep Learning0
Compressively Sensed Image Recognition0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DMP-DUN-Plus (4-step)Average PSNR42.82Unverified
2AMPA-NetAverage PSNR40.32Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR36.33Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR35.95Unverified
#ModelMetricClaimedVerifiedStatus
1AMPA-NetAverage PSNR35.86Unverified