Unrolled Optimization With Deep Learning-Based Priors for Phaseless Inverse Scattering Problems-Reference-Cited by-同舟云学术

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Unrolled Optimization With Deep Learning-Based Priors for Phaseless Inverse Scattering Problems

Published:2022 Issue: Volume:60 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Deshmukh Samruddhi¹^ORCID,Dubey Amartansh¹^ORCID,Murch Ross²^ORCID

Affiliation:

1. Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology (HKUST), Sai Kung, Hong Kong

2. Department of Electronic and Computer Engineering, Institute for Advanced Study, Hong Kong University of Science and Technology (HKUST), Sai Kung, Hong Kong

Funder

Hong Kong Research Grants Council with the Collaborative Research Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09919195.pdf?arnumber=9919195

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Reducing the Number of Measurement Nodes in RF Imaging Using Antenna-Pattern Diversity With an Extended Rytov Approximation;IEEE Transactions on Antennas and Propagation;2023-11

2. Reconciling Radio Tomographic Imaging with Phaseless Inverse Scattering;IEEE Transactions on Antennas and Propagation;2023

3. ATASI-Net: An Efficient Sparse Reconstruction Network for Tomographic SAR Imaging With Adaptive Threshold;IEEE Transactions on Geoscience and Remote Sensing;2023

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