Tropical cyclone intensity estimation through convolutional neural network transfer learning using two geostationary satellite datasets

Tropical cyclone intensity estimation through convolutional neural network transfer learning using two geostationary satellite datasets

Accurate prediction and monitoring of tropical cyclone (TC) intensity are crucial for saving lives, mitigating damages, and improving disaster response measures. In this study, we used a convolutional neural network (CNN) model to estimate TC intensity in the western North Pacific using Geo-KOMPSAT-...

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Bibliographic Details
Main Authors: Hyeyoon Jung, You-Hyun Baek, Il-Ju Moon, Juhyun Lee, Eun-Ha Sohn
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-01-01
Series:Frontiers in Earth Science
Subjects:
tropical cyclone intensity
artificial intelligence
transfer learning
convolutional neural network
geostationary satellite data
Online Access:https://www.frontiersin.org/articles/10.3389/feart.2023.1285138/full

Internet

https://www.frontiersin.org/articles/10.3389/feart.2023.1285138/full

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