Transfer Learning-Based Generative Adversarial Network Model for Tropical Cyclone Wind Speed Reconstruction From SAR Images-Reference-Cited by-同舟云学术

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Transfer Learning-Based Generative Adversarial Network Model for Tropical Cyclone Wind Speed Reconstruction From SAR Images

Published:2024 Issue: Volume:62 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Li Xiaohui¹^ORCID,Han Xinhai¹^ORCID,Yang Jingsong¹^ORCID,Wang Jiuke²,Han Guoqi³^ORCID

Affiliation:

1. State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China

2. School of Artificial Intelligence, Sun Yat-sen University, Zhuhai, China

3. Fisheries and Oceans Canada, Institute of Ocean Sciences, Sidney, BC, Canada

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

SINOPEC Shengli Oilfield Company Research Projects

Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10504291.pdf?arnumber=10504291

Reference54 articles.

1. The Maximum Intensity of Hurricanes

2. Cyclone track forecasting based on satellite images using artificial neural networks

3. Hurricane Forecasting: A Novel Multimodal Machine Learning Framework

4. Hurricane Damage Detection using Machine Learning and Deep Learning Techniques: A Review

5. Monitoring hurricanes over the ocean with wide swath SAR;Friedman;Johns Hopkins APL Tech. Dig.,2000

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