D3C2-Net: Dual-Domain Deep Convolutional Coding Network for Compressive Sensing
By mapping iterative optimization algorithms into neural networks (NNs), deep unfolding
networks (DUNs) exhibit well-defined and interpretable structures and achieve remarkable …
networks (DUNs) exhibit well-defined and interpretable structures and achieve remarkable …
UFC-Net: Unrolling Fixed-point Continuous Network for Deep Compressive Sensing
X Wang, H Gan - Proceedings of the IEEE/CVF Conference …, 2024 - openaccess.thecvf.com
Deep unfolding networks (DUNs) renowned for their interpretability and superior
performance have invigorated the realm of compressive sensing (CS). Nonetheless existing …
performance have invigorated the realm of compressive sensing (CS). Nonetheless existing …
MTC-CSNet: Marrying Transformer and Convolution for Image Compressed Sensing
M Shen, H Gan, C Ma, C Ning, H Li… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Image compressed sensing (ICS) has been extensively applied in various imaging domains
due to its capability to sample and reconstruct images at subNyquist sampling rates. The …
due to its capability to sample and reconstruct images at subNyquist sampling rates. The …
NesTD-Net: Deep NESTA-Inspired Unfolding Network With Dual-Path Deblocking Structure for Image Compressive Sensing
Deep compressive sensing (CS) has become a prevalent technique for image acquisition
and reconstruction. However, existing deep learning (DL)-based CS methods often …
and reconstruction. However, existing deep learning (DL)-based CS methods often …
Dual-Domain Feature Fusion and Multi-Level Memory-Enhanced Network for Spectral Compressive Imaging
Y Ying, J Wang, Y Shi, N Ling… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In the Coded Aperture Snapshot Spectral Imaging (CASSI) systems, hyperspectral images
(HSIs) reconstruction methods are employed to recover 3D signals from 2D compressive …
(HSIs) reconstruction methods are employed to recover 3D signals from 2D compressive …