Deep Learning-Based Metasurface Design Platform with Self-Data Generation

Ki Won Jeong, Yun Seon Do

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

Abstract

Design parameters of metasurfaces representing the desired color were extracted through a deep learning based design platform. In addition, design accuracy was increased with self-generated data during the validation process.

Original languageEnglish
Title of host publication16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350372076
DOIs
StatePublished - 2024
Event16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024 - Incheon, Korea, Republic of
Duration: 4 Aug 20249 Aug 2024

Publication series

Name16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

Conference

Conference16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024
Country/TerritoryKorea, Republic of
CityIncheon
Period4/08/249/08/24

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