Single-Pixel Machine Vision Using Spectral Encoding through Diffractive Optical Networks

Jingxi Li, Deniz Mengu, Nezih T. Yardimci, Yi Luo, Xurong Li, Muhammed Veli, Yair Rivenson, Mona Jarrahi, Aydogan Ozcan

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

Abstract

We present and experimentally demonstrate a deep learning-driven machine-vision framework that trains diffractive surfaces to encode the spatial information objects into the output power spectrum for all-optical image classification using a single-pixel spectroscopic detector.

Original languageEnglish
Title of host publication2021 Conference on Lasers and Electro-Optics, CLEO 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9781943580910
StatePublished - 1 May 2021
Externally publishedYes
Event2021 Conference on Lasers and Electro-Optics, CLEO 2021 - Virtual, Online, United States
Duration: 9 May 202114 May 2021

Publication series

Name2021 Conference on Lasers and Electro-Optics, CLEO 2021 - Proceedings

Conference

Conference2021 Conference on Lasers and Electro-Optics, CLEO 2021
Country/TerritoryUnited States
CityVirtual, Online
Period9/05/2114/05/21

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Instrumentation
  • Atomic and Molecular Physics, and Optics

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