paper
2016
Observations & remote sensing
Post-processing & calibration New model or method
Other Journal
2016-03-02
026
Mar 2016
Yumeng Tao, Xiaogang Gao, Kuolin Hsu et al.
Journal of Hydrometeorology
A stacked denoising autoencoder bias-corrects PERSIANN-CCS satellite rainfall, cutting precipitation-rate bias by 78–98% and false alarms by 33–43%.
Observations & remote sensingClassic
A Deep Neural Network Modeling Framework to Reduce Bias in Satellite Precipitation Products
In one sentence. A stacked denoising autoencoder bias-corrects PERSIANN-CCS satellite rainfall, cutting precipitation-rate bias by 78–98% and false alarms by 33–43%.
Labels
- Topic
- Observations & remote sensing, Post-processing & calibration
- Type
- New model or method
- Method
- Other
- Domain
- Regional
- Data
- Satellite, Radar
- Status
- Research
- Identifiers
- DOI:10.1175/jhm-d-15-0075.1 OpenAlex:W2232647241
- Added
- 2026-10-22
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