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Microstructure Quantification With Deep Learning Encoders Pre-Trained on a Massive Microscopy Dataset
Document ID
20230008016
Acquisition Source
Glenn Research Center
Document Type
Presentation
Authors
Joshua Stuckner (Glenn Research Center Cleveland, Ohio, United States)
Date Acquired
May 23, 2023
Subject Category
Mathematical and Computer Sciences (General)
Chemistry and Materials (General)
Meeting Information
Meeting: International Materials, Applications, and Technologies (IMAT 2023)
Location: Detroit, MI
Country: US
Start Date: October 16, 2023
End Date: October 19, 2023
Sponsors: ASM International
Funding Number(s)
WBS: 109492.02.03.05.02
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Technical Review
Single Expert
Keywords
machine learning
neural networks
deep learning
microscopy analysis

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