Improving robustness for model discerning synthesis process of uranium oxide with unsupervised domain adaptation

Improving robustness for model discerning synthesis process of uranium oxide with unsupervised domain adaptation

The quantitative characterization of surface structures captured in scanning electron microscopy (SEM) images has proven to be effective for discerning provenance of an unknown nuclear material. Recently, many works have taken advantage of the powerful performance of convolutional neural networks (C...

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Bibliographic Details
Main Authors: Cuong Ly, Cody Nizinski, Alex Hagen, Luther W McDonald, Tolga Tasdizen
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-10-01
Series:Frontiers in Nuclear Engineering
Subjects:
nuclear forensics
machine learning
convolutional neural networks
domain adaptation
scanning electron microscopy
Online Access:https://www.frontiersin.org/articles/10.3389/fnuen.2023.1230052/full

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