Reconstruction of the Regional Total Electron Content Maps Over the Korean Peninsula Using Deep Convolutional Generative Adversarial Network and Poisson Blending-Reference-Cited by-同舟云学术

Reconstruction of the Regional Total Electron Content Maps Over the Korean Peninsula Using Deep Convolutional Generative Adversarial Network and Poisson Blending

Published:2022-08 Issue:8 Volume:20 Page:
ISSN:1542-7390
Container-title:Space Weather
language:en
Short-container-title:Space Weather

Author:

Jeong Se‐Heon¹²^ORCID,Lee Woo Kyoung²³^ORCID,Jang Soojeong⁴^ORCID,Kil Hyosub⁵^ORCID,Kim Jeong‐Heon²^ORCID,Kwak Young‐Sil²³^ORCID,Kim Yong Ha¹^ORCID,Hong Junseok²^ORCID,Choi Byung‐Kyu²^ORCID

Affiliation:

1. Chungnam National University Daejeon South Korea

2. Korea Astronomy and Space Science Institute Daejeon South Korea

3. Korea University of Science and Technology Daejeon South Korea

4. Kyung Hee University Yongin South Korea

5. Johns Hopkins University Applied Physics Laboratory Laurel MD USA

Funder

Korea Astronomy and Space Science Institute

National Science Foundation

Multidisciplinary University Research Initiative

Asian Office of Aerospace Research and Development

National Research Foundation of Korea

Publisher

American Geophysical Union (AGU)

Subject

Atmospheric Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2022SW003131

Reference29 articles.

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4. The Application of a Deep Convolutional Generative Adversarial Network on Completing Global TEC Maps

5. Improvement of a Deep Learning Algorithm for Total Electron Content Maps: Image Completion

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