paper
2021
Extremes & hazards
Observations & remote sensing New model or method
CNN / U-NetNOAA (incl. GFDL, PSL, GSL, NCEP/EMC) Journal
2021-03-26
061
Mar 2021
Chong Wang, Gang Zheng, Xiaofeng Li et al.
IEEE Transactions on Geoscience and Remote Sensing
NOAA (incl. GFDL, PSL, GSL, NCEP/EMC)
CNNs estimate western North Pacific tropical cyclone intensity from Himawari-8 infrared images, reaching 88.9% accuracy and 4.62 m/s RMSE with focal loss and binary framing.
Tropical Cyclone Intensity Estimation From Geostationary Satellite Imagery Using Deep Convolutional Neural Networks
In one sentence. CNNs estimate western North Pacific tropical cyclone intensity from Himawari-8 infrared images, reaching 88.9% accuracy and 4.62 m/s RMSE with focal loss and binary framing.
Labels
- Topic
- Extremes & hazards, Observations & remote sensing
- Type
- New model or method
- Method
- CNN / U-Net
- Domain
- Regional
- Data
- Satellite
- Status
- Research
- Identifiers
- DOI:10.1109/tgrs.2021.3066299 OpenAlex:W3143274035
- Added
- 2026-10-22
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