paper
2019
Observations & remote sensing
New model or method
CNN / U-Net Journal
2019-11-27
030
Nov 2019
Mojtaba Sadeghi, Ata Akbari Asanjan, Mohammad Faridzad et al.
Journal of Hydrometeorology
PERSIANN-CNN applies CNNs to geostationary infrared and water vapor channels, beating PERSIANN-CCS by 54% in CSI and cutting RMSE by 37%.
PERSIANN-CNN: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Convolutional Neural Networks
In one sentence. PERSIANN-CNN applies CNNs to geostationary infrared and water vapor channels, beating PERSIANN-CCS by 54% in CSI and cutting RMSE by 37%.
Labels
- Topic
- Observations & remote sensing
- Type
- New model or method
- Method
- CNN / U-Net
- Domain
- Regional
- Data
- Satellite, Radar
- Status
- Research
- Identifiers
- DOI:10.1175/jhm-d-19-0110.1 OpenAlex:W2977666392
- Added
- 2026-10-22
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