Skip to main navigation Skip to search Skip to main content

Optimized Design of Thick Holography Based on Deep Learning and Fourier Modal Method

  • Nanxing Chen*
  • , Yubin Cao
  • , Jiandong Meng
  • , Jianyi Li
  • , Qingbo Yang
  • , Kairui Cao
  • *Corresponding author for this work

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

Abstract

This paper introduces a deep neural network architecture, which is inspired by the Fourier modal method, facilitating layered iterative processing of thick holography to achieve high diffraction efficiency.

Original languageEnglish
Title of host publicationQuantum Sensing and Metrology, QSM 2024 in Proceedings Optica Sensing Congress 2024, AIS, LACSEA, Sensors, QSM - Part of Optica Sensing Congress
PublisherOptical Society of America
ISBN (Electronic)9781957171364
DOIs
StatePublished - 2024
EventQuantum Sensing and Metrology, QSM 2024 - Part of Optica Sensing Congress - Toulouse, France
Duration: 15 Jul 202419 Jul 2024

Publication series

NameQuantum Sensing and Metrology, QSM 2024 in Proceedings Optica Sensing Congress 2024, AIS, LACSEA, Sensors, QSM - Part of Optica Sensing Congress

Conference

ConferenceQuantum Sensing and Metrology, QSM 2024 - Part of Optica Sensing Congress
Country/TerritoryFrance
CityToulouse
Period15/07/2419/07/24

Cite this