Resolution enhancement in scanning electron microscopy using deep learning

  • Kevin de Haan
  • , Zachary S. Ballard
  • , Yair Rivenson
  • , Yichen Wu
  • , Aydogan Ozcan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present a deep learning-based framework to perform image super-resolution in scanning electron microscopy. The technique was demonstrated to perform a resolution enhancement using a standard resolution test target and hydrogel samples.

Original languageEnglish
Title of host publicationCLEO
Subtitle of host publicationScience and Innovations, CLEO_SI 2020
PublisherOptica Publishing Group (formerly OSA)
ISBN (Print)9781943580767
DOIs
StatePublished - 1 Jan 2020
Externally publishedYes
EventCLEO: Science and Innovations, CLEO_SI 2020 - Washington, United States
Duration: 10 May 202015 May 2020

Publication series

NameOptics InfoBase Conference Papers
VolumePart F183-CLEO-SI 2020
ISSN (Electronic)2162-2701

Conference

ConferenceCLEO: Science and Innovations, CLEO_SI 2020
Country/TerritoryUnited States
CityWashington
Period10/05/2015/05/20

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

Fingerprint

Dive into the research topics of 'Resolution enhancement in scanning electron microscopy using deep learning'. Together they form a unique fingerprint.

Cite this