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 201–225 of 597 papers

TitleStatusHype
Robust Symbol Detection in Overloaded NOMA Systems—0
Disentangling coincident cell events using deep transfer learning and compressive sensing—0
DeepCodec: Adaptive Sensing and Recovery via Deep Convolutional Neural Networks—0
On Distributed Non-convex Optimization: Projected Subgradient Method For Weakly Convex Problems in Networks—0
Distributed Video Adaptive Block Compressive Sensing—0
Downlink Massive MIMO Channel Estimation via Deep Unrolling : Sparsity Exploitations in Angular Domain—0
Deep Attentive Wasserstein Generative Adversarial Networks for MRI Reconstruction with Recurrent Context-Awareness—0
Adaptive Temporal Compressive Sensing for Video—0
Dynamic Compressive Sensing based on RLS for Underwater Acoustic Communications—0
A Compressive Sensing Based Method for Harmonic State Estimation—0
Deep ADMM-Net for Compressive Sensing MRI—0
Efficient Fourier single-pixel imaging with Gaussian random sampling—0
Compressive Sensing Based Situational Awareness and Sensor Placement for DC Microgrids with Relatively Fixed Operation Patterns—0
Efficient Recovery of Jointly Sparse Vectors—0
Efficient Sampling for Learning Sparse Additive Models in High Dimensions—0
Electromagnetic Property Sensing: A New Paradigm of Integrated Sensing and Communication—0
Electromagnetic Property Sensing in ISAC with Multiple Base Stations: Algorithm, Pilot Design, and Performance Analysis—0
Energy-aware adaptive bi-Lipschitz embeddings—0
Enhanced block sparse signal recovery based on q-ratio block constrained minimal singular values—0
Data-Driven Forecast of Dengue Outbreaks in Brazil: A Critical Assessment of Climate Conditions for Different Capitals—0
Error Resilient Deep Compressive Sensing—0
Estimating Sparsity Level for Enabling Compressive Sensing of Wireless Channels and Spectra in 5G and Beyond—0
Estimation with Low-Rank Time-Frequency Synthesis Models—0
Evaluation of the Effects of Compressive Spectrum Sensing Parameters on Primary User Behavior Estimation—0
Data-Driven Deep Learning to Design Pilot and Channel Estimator For Massive MIMO—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