Deep Learning for Sensing Matrix Prediction in Computational Microwave Imaging With Coded-Apertures

Deep Learning for Sensing Matrix Prediction in Computational Microwave Imaging With Coded-Apertures

This work aims to simplify the characterization process of coded-apertures for computational imaging (CI) at microwave frequencies. A major benefit of the presented technique is the minimization of the processing time needed to calculate the system sensing matrix for microwave CI-based compressive s...

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Bibliographic Details
Main Authors: Jiaming Zhang, Rahul Sharma, Maria Garcia-Fernandez, Guillermo Alvarez-Narciandi, Muhammad Ali Babar Abbasi, Okan Yurduseven
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Computational imaging
deep learning
image reconstruction
microwave imaging
sensing matrix
Online Access:https://ieeexplore.ieee.org/document/10415384/

Internet

https://ieeexplore.ieee.org/document/10415384/

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