Papers with Code · CC BY-SA 4.0

Compressive Sensing

6 평가 기록 5 datasets

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.

<span class="description-source">Source: Sparse Estimation with Generalized Beta Mixture and the Horseshoe Prior </span>

논문

AMPA-Net: Optimization-Inspired Attention Neural Network for Deep Compressed Sensing

2010.06907 2020-10-14 이 페이지의 평가 4건

Average PSNR: 40.32

An efficient deep convolutional laplacian pyramid architecture for CS reconstruction at low sampling ratios

1804.04970 2018-04-13 이 페이지의 평가 1건

Average PSNR: improving about 0.2-0.3dB

Using Powerful Prior Knowledge of Diffusion Model in Deep Unfolding Networks for Image Compressive Sensing

2503.08429 2025-03-11 이 페이지의 평가 1건

Average PSNR: 42.82PSNR: 42.82