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An AI Based System for Objective Tropical Cyclone Intensity EstimationNo abstract available
Document ID
20190001209
Acquisition Source
Marshall Space Flight Center
Document Type
Presentation
Authors
Miller, Jeffrey
(Alabama Univ. Huntsville, AL, United States)
Maskey, Manil
(NASA Marshall Space Flight Center Huntsville, AL, United States)
Ramachandran, Rahul
(NASA Marshall Space Flight Center Huntsville, AL, United States)
Gurung, Iksha
(Alabama Univ. Huntsville, AL, United States)
Freitag, Brian
(Alabama Univ. Huntsville, AL, United States)
Bollinger, Drew
(Development Seed Washington, DC, United States)
Mestre, Ricardo
(Development Seed Washington, DC, United States)
da Silva, Daniel
(Development Seed Washington, DC, United States)
Molthan, Andrew
(NASA Marshall Space Flight Center Huntsville, AL, United States)
Hain, Christopher
(NASA Marshall Space Flight Center Huntsville, AL, United States)
Cecil, Dan
(NASA Marshall Space Flight Center Huntsville, AL, United States)
Date Acquired
March 4, 2019
Publication Date
January 6, 2019
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
MSFC-E-DAA-TN64167
Meeting Information
Meeting: American Meteorological Society (AMS) Annual Meeting
Location: Phoenix, AZ
Country: United States
Start Date: January 6, 2019
End Date: January 10, 2019
Sponsors: American Meteorological Society (AMS)
Funding Number(s)
CONTRACT_GRANT: NNM11AA01A
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
Keywords
Deep Learning
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