Measurement of Leakage Radiation from Random Nanoislands for Machine Learning-Based Prediction

Hongki Lee, Seongmin Im, Sukhyeon Ka, Jooyoung Kim, Jaekwon Lee, Kar Ann Toh, Donghyun Kim

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

Abstract

This work addresses measurement of leakage radiation characteristics for prediction of far-field images of random nanoisland structures. Leakage radiation images as well as morphology of nanoislands were used to obtain correlation based on machine learning models and compared.

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
Publication statusPublished - 2024
Event16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024 - Incheon, Korea, Republic of
Duration: 2024 Aug 42024 Aug 9

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
Period24/8/424/8/9

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Atomic and Molecular Physics, and Optics

Fingerprint

Dive into the research topics of 'Measurement of Leakage Radiation from Random Nanoislands for Machine Learning-Based Prediction'. Together they form a unique fingerprint.

Cite this