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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 361–370 of 597 papers

TitleStatusHype
Hyperspectral Compressive Sensing Using Manifold-Structured Sparsity Prior—0
Hyperspectral image reconstruction for spectral camera based on ghost imaging via sparsity constraints using V-DUnet—0
ICRICS: Iterative Compensation Recovery for Image Compressive Sensing—0
Identifying Unused RF Channels Using Least Matching Pursuit—0
_1DecNet+: A new architecture framework by _1 decomposition and iteration unfolding for sparse feature segmentation—0
Image Classification with A Deep Network Model based on Compressive Sensing—0
Image Compression Based on Compressive Sensing: End-to-End Comparison with JPEG—0
Image Compressive Sensing Recovery Using Adaptively Learned Sparsifying Basis via L0 Minimization—0
Image Reconstruction from Undersampled Confocal Microscopy Data using Multiresolution Based Maximum Entropy Regularization—0
Image Reconstruction using Matched Wavelet Estimated from Data Sensed Compressively using Partial Canonical Identity Matrix—0
Show:102550
← PrevPage 37 of 60Next →
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