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 376–400 of 597 papers

TitleStatusHype
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
A Survey: Non-Orthogonal Multiple Access with Compressed Sensing Multiuser Detection for mMTC—0
Multi-Scale Deep Compressive Sensing NetworkCode0
Fast Signal Recovery from Saturated Measurements by Linear Loss and Nonconvex Penalties—0
Compressive Hyperspectral Imaging: Fourier Transform Interferometry meets Single Pixel Camera—0
Joint optimization for compressive video sensing and reconstruction under hardware constraints—0
Theoretical Linear Convergence of Unfolded ISTA and its Practical Weights and ThresholdsCode0
Comparative Study on Millimeter Wave Location-Based Beamforming—0
A Survey on Nonconvex Regularization Based Sparse and Low-Rank Recovery in Signal Processing, Statistics, and Machine LearningCode0
Experimental Results of a 3D Millimeter-Wave Compressive-Reflector-Antenna Imaging System—0
LAPRAN: A Scalable Laplacian Pyramid Reconstructive Adversarial Network for Flexible Compressive Sensing ReconstructionCode0
Convolutional sparse coding for capturing high speed video content—0
Training deep learning based image denoisers from undersampled measurements without ground truth and without image prior—0
Depth and Transient Imaging With Compressive SPAD Array Cameras—0
Stochastic Deep Compressive Sensing for the Reconstruction of Diffusion Tensor Cardiac MRI—0
Frequency-modulated continuous-wave LiDAR compressive depth-mapping—0
Active User Detection of Uplink Grant-Free SCMA in Frequency Selective Channel—0
Compressive Sensing Imaging of 3-D Object by a Holographic Algorithm—0
Estimation with Low-Rank Time-Frequency Synthesis Models—0
An efficient deep convolutional laplacian pyramid architecture for CS reconstruction at low sampling ratiosCode0
Kinetic 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