The Application of a Deep Convolutional Generative Adversarial Network on Completing Global TEC Maps-Reference-Cited by-同舟云学术

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

Published:2021-03 Issue:3 Volume:126 Page:
ISSN:2169-9380
Container-title:Journal of Geophysical Research: Space Physics
language:en
Short-container-title:JGR Space Physics

Author:

Chen Jie¹^ORCID,Fang Hanxian¹^ORCID,Liu Zhendi¹^ORCID

Affiliation:

1. College of Meteorology and Oceanography National University of Defense Technology Nanjing China

Funder

National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

Subject

Space and Planetary Science,Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2020JA028418

Reference23 articles.

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

2. The CNN paradigm

3. Space Weather and the Global Positioning System

4. Graph Laplace for Occluded Face Completion and Recognition

5. The International GPS Service (IGS) Ionosphere Working Group

Cited by 8 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. Deep Learning‐Based Prediction of Global Ionospheric TEC During Storm Periods: Mixed CNN‐BiLSTM Method;Space Weather;2024-07

2. Forecasting of global ionospheric TEC using a deep learning approach;GPS Solutions;2023-02-15

3. Global TEC Map Fusion Through a Hybrid Deep Learning Model: RFGAN;Space Weather;2023-01

4. Global Ionospheric Total Electron Content Completion with a GAN-Based Deep Learning Framework;Remote Sensing;2022-11-29

5. A Machine Learning-Based Method for Modeling TEC Regional Temporal-Spatial Map;Remote Sensing;2022-11-04

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