A novel transmission-augmented deep unfolding network with consideration of residual recovery
Abstract Compressive sensing (CS) has been widely applied in signal processing field, especially for image reconstruction tasks. CS simplifies the sampling and compression procedures, but leaves the difficulty to the nonlinear reconstruction. Traditional CS reconstruction algorithms are usually iter...
Saved in:
Main Authors: | Zhijie Zhang, Huang Bai, Ljubiša Stanković, Junmei Sun, Xiumei Li |
---|---|
Format: | Article |
Language: | English |
Published: |
Springer
2025-01-01
|
Series: | Complex & Intelligent Systems |
Subjects: | |
Online Access: | https://doi.org/10.1007/s40747-024-01727-2 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
IRSnet: An Implicit Residual Solver and Its Unfolding Neural Network With 0.003M Parameters for Total Variation Models
by: Yuanhao Gong
Published: (2025-01-01) -
Deep Unfolding-Aided Parameter Tuning for Plug-and-Play-Based Video Snapshot Compressive Imaging
by: Takashi Matsuda, et al.
Published: (2025-01-01) -
Transmission of unfolded protein response—a regulator of disease progression, severity, and spread in virus infections
by: Vibhu Prasad
Published: (2025-02-01) -
Proton response and neutron spectrum unfolding by solution-grown trans-stilbene scintillator
by: Nguyen Duy Quang, et al.
Published: (2025-01-01) -
Pharmacological Modulation of the Unfolded Protein Response as a Therapeutic Approach in Cutaneous T-Cell Lymphoma
by: Nadia St. Thomas, et al.
Published: (2025-01-01)