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Title: 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.:
PNNL (Pacific Northwest National Laboratory (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 = {2018},
month = {12}
}

Multimedia:

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