paper
2021
Observations & remote sensing
Extremes & hazards New model or method
CNN / U-NetNanjing University of Information Science & Technology (NUIST) Journal
2021-11-09
022
Nov 2021
Mei Xue, Renlong Hang, Xiao–Tong Yuan et al.
IEEE Transactions on Geoscience and Remote Sensing
Nanjing University of Information Science & Technology (NUIST)
A multitask CNN estimates global tropical cyclone precipitation from HURSAT-B1 imagery, reaching 0.68 detection probability and beating MLR and random forest baselines.
Global Tropical Cyclone Precipitation Estimation via a Multitask Convolutional Neural Network Based on HURSAT-B1 Data
In one sentence. A multitask CNN estimates global tropical cyclone precipitation from HURSAT-B1 imagery, reaching 0.68 detection probability and beating MLR and random forest baselines.
Labels
- Topic
- Observations & remote sensing, Extremes & hazards
- Type
- New model or method
- Method
- CNN / U-Net
- Domain
- Global
- Data
- Satellite
- Status
- Research
- Identifiers
- DOI:10.1109/tgrs.2021.3126419 OpenAlex:W3214712601
- Added
- 2026-10-22
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