Deep learning tackles cloud detection
Abstract
To better understand Earth systems, atmospheric scientists use cloud data collected by a remote sensing tool called lidar. These data are an important part of global forecasting, but analyzing lidar images by hand is time-consuming. Researchers at Pacific Northwest National Laboratory teamed up to see if a deep learning model could process lidar data better than current automatic detection techniques.
- Authors:
- Publication Date:
- Research Org.:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1495681
- Resource Type:
- Multimedia
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING; 54 ENVIRONMENTAL SCIENCES; DEEP LEARNING; LIDAR; CLOUD DATA; CLIMATE; ALGORITHMS
Citation Formats
Flynn, Donna, and Cromwell, Erol. Deep learning tackles cloud detection. United States: N. p., 2018.
Web.
Flynn, Donna, & Cromwell, Erol. Deep learning tackles cloud detection. United States.
Flynn, Donna, and Cromwell, Erol. Mon .
"Deep learning tackles cloud detection". United States. https://www.osti.gov/servlets/purl/1495681.
@article{osti_1495681,
title = {Deep learning tackles cloud detection},
author = {Flynn, Donna and Cromwell, Erol},
abstractNote = {To better understand Earth systems, atmospheric scientists use cloud data collected by a remote sensing tool called lidar. These data are an important part of global forecasting, but analyzing lidar images by hand is time-consuming. Researchers at Pacific Northwest National Laboratory teamed up to see if a deep learning model could process lidar data better than current automatic detection techniques.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Dec 10 00:00:00 EST 2018},
month = {Mon Dec 10 00:00:00 EST 2018}
}