Reaping the benefits of machine learning pattern recognition in nanophotonic component design

From National Research Council Canada

DOIResolve DOI: https://doi.org/10.1117/12.2506787
AuthorSearch for: 1 ; Search for: 2 ; Search for: 2 ; Search for: 2 ; Search for: 2 ; Search for: 2 ; Search for: ; Search for: ; Search for: ; Search for: ; Search for: 2 
EditorSearch for: García-Blanco, Sonia M.; Search for: Cheben, Pavel2 
Name affiliation
  1. National Research Council Canada. Digital Technologies
  2. National Research Council Canada. Advanced Electronics and Photonics
FormatText
TypeArticle
Proceedings titleIntegrated Optics: Devices, Materials, and Technologies XXIII
Series titleProceedings of SPIE; no. 10921
ConferenceIntegrated Optics: Devices, Materials, and Technologies XXIII, February 2-7, 2019, San Francisco, USA
ISSN0277-786X
1996-756X
ISBN9781510624849
9781510624856
Pages10
Subjectmachine learning; optical design; silicon; nanophotonics; metamaterials; pattern recognition; principal component analysis
Abstract
Publication date
PublisherSPIE
LanguageEnglish
Peer reviewedYes
Export citationExport as RIS
Report a correctionReport a correction
Record identifierfce6446a-ab1d-4404-8411-faa628cf6fad
Record created2019-03-12
Record modified2019-03-12
Date modified: