Machine Learning for Wavefront Sensing

Alison P. Wong, Barnaby R.M. Norris, Vincent Deo, Olivier Guyon, Peter G. Tuthill, Julien Lozi, Sébastien Vievard, Kyohoon Ahn

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

5 Scopus citations

Abstract

Advances in the field of deep learning have motivated a flurry of research into the application of neural networks to wavefront sensing for adaptive optics. This paper gives an overview of current research in this area, highlighting new methods in deep learning that wavefront sensing stands to improve from. Finally we discuss future endeavours and speculate on how deep learning is expected to impact the field of wavefront sensing.

Original languageEnglish (US)
Title of host publicationAdaptive Optics Systems VIII
EditorsLaura Schreiber, Dirk Schmidt, Elise Vernet
PublisherSPIE
ISBN (Electronic)9781510653511
DOIs
StatePublished - 2022
EventAdaptive Optics Systems VIII 2022 - Montreal, Canada
Duration: Jul 17 2022Jul 22 2022

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12185
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceAdaptive Optics Systems VIII 2022
Country/TerritoryCanada
CityMontreal
Period7/17/227/22/22

Keywords

  • adaptive optics
  • deep learning
  • machine learning
  • neural networks
  • wavefront sensors

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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