paper
2022
Observations & remote sensing
New model or method
CNN / U-Net Journal
2022-04-22
016
Apr 2022
Liang Mei, Xiaoqi Wang, Zhenfeng Gong et al.
Optics Express
A VGG16-based CNN applied to wavelet covariance transform images retrieves planetary boundary layer height from lidar profiles without human intervention, validated against radiosondes and MPLNET.
Retrieval of the planetary boundary layer height from lidar measurements by a deep-learning method based on the wavelet covariance transform
In one sentence. A VGG16-based CNN applied to wavelet covariance transform images retrieves planetary boundary layer height from lidar profiles without human intervention, validated against radiosondes and MPLNET.
Labels
- Topic
- Observations & remote sensing
- Type
- New model or method
- Method
- CNN / U-Net
- Domain
- Local / station
- Data
- Station / in-situ, Other
- Status
- Research
- Identifiers
- DOI:10.1364/oe.454094 OpenAlex:W4224257022
- Added
- 2026-10-22
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