Complex-Valued End-to-End Deep Network With Coherency Preservation for Complex-Valued SAR Data Reconstruction and Classification-Reference-Cited by-同舟云学术

Complex-Valued End-to-End Deep Network With Coherency Preservation for Complex-Valued SAR Data Reconstruction and Classification

Published:2023 Issue: Volume:61 Page:1-17
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Mohammadi Asiyabi Reza¹^ORCID,Datcu Mihai¹^ORCID,Anghel Andrei¹^ORCID,Nies Holger²^ORCID

Affiliation:

1. Center for Spatial Information (CEOSpaceTech), University POLITEHNICA of Bucharest (UPB), Bucharest, Romania

2. Center for Sensor Systems (ZESS), University of Siegen, Siegen, Germany

Funder

European Union’s Horizon 2020 Research and Innovation Programme

Marie Skłodowska-Curie

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10102460.pdf?arnumber=10102460

Reference64 articles.

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2. High-resolution representations for labeling pixels and regions;sun;arXiv 1904 04514,2019

3. Complex-Valued Convolutional Neural Network and Its Application in Polarimetric SAR Image Classification

4. S1SLC_CVDL: A complex-valued annotated single look complex Sentinel-1 SAR dataset for complex-valued deep networks;reza mohammadi asiyabi;IEEE Dataport,2023

5. Complex-Valued Convolutional Autoencoder and Spatial Pixel-Squares Refinement for Polarimetric SAR Image Classification

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