Deep learning, dynamic sampling and smart energy-dispersive spectroscopy

Yan Zhang, G. M. Dilshan Godaliyadda, Nicola Ferrier, Emine B. Gulsoy, Charles A. Bouman, Charudatta Phatak*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A convolutional neural network (CNN) classifier is trained using simulated energy-dispersive spectroscopy data. The CNN incorporated within a dynamic sampling method is to reduce radiation exposure and data acquisition time for elemental mapping.

Original languageEnglish (US)
Title of host publicationFrontiers in Optics, FiO 2017
PublisherOSA - The Optical Society
ISBN (Electronic)9781557528209
DOIs
StatePublished - Jan 1 2017
EventFrontiers in Optics, FiO 2017 - Washington, United States
Duration: Sep 18 2017Sep 21 2017

Publication series

NameOptics InfoBase Conference Papers
VolumePart F66-FiO 2017

Other

OtherFrontiers in Optics, FiO 2017
CountryUnited States
CityWashington
Period9/18/179/21/17

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

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