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Using Deep Learning for Tropical Cyclone Intensity Estimation
NTRS Full-Text: Click to View  [PDF Size: 2.3 MB]
Author and Affiliation:
Miller, J. J.(Alabama Univ., Huntsville, AL, United States)
Maskey, Manil(NASA Marshall Space Flight Center, Huntsville, AL, United States)
Berendes, Todd(Alabama Univ., Huntsville, AL, United States)
Abstract: No abstract available
Publication Date: Dec 11, 2017
Document ID:
20170011716
(Acquired Dec 14, 2017)
Subject Category: METEOROLOGY AND CLIMATOLOGY
Report/Patent Number: MSFC-E-DAA-TN49822
Document Type: Oral/Visual Presentation
Meeting Information: American Geophysical Union (AGU) Meeting; 11-15 Dec. 2017; New Orleans, LA; United States
Meeting Sponsor: American Geophysical Union; Washington, DC, United States
Contract/Grant/Task Num: NNM11AA01A
Financial Sponsor: NASA Marshall Space Flight Center; Huntsville, AL, United States
Organization Source: NASA Marshall Space Flight Center; Huntsville, AL, United States
Description: 17p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright; Public use permitted
NASA Terms: TROPICAL STORMS; CYCLONES; WIND VELOCITY; ESTIMATING; MICROWAVE IMAGERY; NEURAL NETS; DATA ACQUISITION
Other Descriptors: DEEP LEARNING; TROPICAL CYCLONE INTENSITY ESTIMATIO
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