Deepti: Deep-Learning-Based Tropical Cyclone Intensity Estimation System
Author:
Funder
NASA Earth Science Data Systems Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Atmospheric Science,Computers in Earth Sciences
Link
http://xplorestaging.ieee.org/ielx7/4609443/8994817/09149719.pdf?arnumber=9149719
Cited by 33 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
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2. A Multiscale and Multilayer Feature Extraction Network With Dual Attention for Tropical Cyclone Intensity Estimation;IEEE Transactions on Geoscience and Remote Sensing;2024
3. SAAC-Net: deep neural network-based model for atmospheric correction in remote sensing;International Journal of Remote Sensing;2023-11-30
4. Cyclone Intensity Estimation Using CNN;2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS);2023-10-18
5. Enhancing Cyclone Intensity Prediction for Smart Cities Using a Deep-Learning Approach for Accurate Prediction;Atmosphere;2023-10-16
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