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DELTA: An Open-Source Framework to Simplify Machine Learning with Satellite ImageryDELTA (Deep Earth Learning, Tools, and Analysis) is an open-source framework developed at NASA to simplify running and training machine learning (ML) models on satellite imagery. Users new to machine learning can run existing ML models on satellite imagery with minimal setup and configuration. For experienced ML users, DELTA helps simplify data engineering, preprocessing steps, and reduces the need for boilerplate code that needs written to make satellite imagery datasets palatable for machine learning. This lets data scientists focus on model development while DELTA handles the imagery manipulation. This presentation will demonstrate DELTA’s functionality and share some examples from an active project using it for flood mapping using imagery from multiple satellite sources.
Document ID
20210025644
Acquisition Source
Ames Research Center
Document Type
Presentation
Authors
Michael von Pohle
(Universities Space Research Association Columbia, Maryland, United States)
Brian Coltin
(Wyle (United States) El Segundo, California, United States)
Scott Mcmichael
(KBR (United States) Houston, Texas, United States)
Date Acquired
December 8, 2021
Subject Category
Earth Resources And Remote Sensing
Mathematical And Computer Sciences (General)
Report/Patent Number
IN44A-08
Meeting Information
Meeting: AGU 2021 Fall Meeting
Location: New Orleans, LA
Country: US
Start Date: December 13, 2021
End Date: December 17, 2021
Sponsors: American Geophysical Union
Funding Number(s)
CONTRACT_GRANT: NNA16BD14C
CONTRACT_GRANT: 80ARC020D0010
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Keywords
deep learning
machine learning
remote sensing
satellite imagery
software framework
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