SALSA-Net: Explainable Deep Unrolling Networks for Compressed Sensing
Deep unrolling networks (DUNs) have emerged as a promising approach for solving compressed sensing (CS) problems due to their superior explainability, speed, and performance compared to classical deep network models. However, the CS performance in terms of efficiency and accuracy remains a principal...
Main Authors: | Heping Song, Qifeng Ding, Jingyao Gong, Hongying Meng, Yuping Lai |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-05-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/23/11/5142 |
Similar Items
-
Deep Unrolling for Light Field Compressed Acquisition Using Coded Masks
by: Guillaume Le Guludec, et al.
Published: (2022-01-01) -
Federated End-to-End Unrolled Models for Magnetic Resonance Image Reconstruction
by: Brett R. Levac, et al.
Published: (2023-03-01) -
Advancing Sensor-Data Based PAT Image Reconstruction Through Efficient and Intelligible Unrolled Networks
by: Mary John, et al.
Published: (2023-01-01) -
IVIU-Net: Implicit Variable Iterative Unrolling Network for Hyperspectral Sparse Unmixing
by: Yuantian Shao, et al.
Published: (2023-01-01) -
Unrolled Algorithms for Group Synchronization
by: Noam Janco, et al.
Published: (2023-01-01)