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Deep Learning for Environmental and Ecological Prediction, Evaluation and Insight With Ensembles of Water Quality (Deep-View)
Document ID
20230011497
Acquisition Source
Goddard Space Flight Center
Document Type
Presentation
Authors
Stephanie Schollaert Uz (Goddard Space Flight Center Greenbelt, Maryland, United States)
Troy Ames (Goddard Space Flight Center Greenbelt, Maryland, United States)
J. Blake Clark (University of Maryland, Baltimore County Baltimore, Maryland, United States)
Dirk Aurin (Morgan State University Baltimore, Maryland, United States)
Date Acquired
August 3, 2023
Publication Date
August 21, 2023
Publication Information
Subject Category
Earth Resources and Remote Sensing
Systems Analysis and Operations Research
Meeting Information
Meeting: Advanced Information Systems Technology (AIST) Grouped Annual Project Reviews
Location: Virtual
Country: US
Start Date: August 21, 2023
Sponsors: National Aeronautics and Space Administration
Funding Number(s)
WBS: 430728.02.21.51.08
CONTRACT_GRANT: 80NSSC22M0001
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
NASA Peer Committee

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