Application of deep learning to direct and inverse problems in plasmonic coloring

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Authors

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  • University of Ottawa
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Details

Original languageEnglish
Title of host publication2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (electronic)9781943580576
Publication statusPublished - May 2019
Externally publishedYes
Event2019 Conference on Lasers and Electro-Optics, CLEO 2019 - San Jose, United States
Duration: 5 May 201910 May 2019

Publication series

NameConference on Lasers and Electro-Optics

Abstract

Laser pulses can color noble metals by inducing nanoparticles on their surface. We apply deep learning to solve the direct and inverse problems which link nanoparticle distributions and laser parameters to the produced colour.

ASJC Scopus subject areas

Cite this

Application of deep learning to direct and inverse problems in plasmonic coloring. / Baxter, Josh; Lesina, Antonino Cala; Guay, Jean Michel et al.
2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8750346 (Conference on Lasers and Electro-Optics).

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Baxter, J, Lesina, AC, Guay, JM, Weck, A, Berini, P & Ramunno, L 2019, Application of deep learning to direct and inverse problems in plasmonic coloring. in 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings., 8750346, Conference on Lasers and Electro-Optics, Institute of Electrical and Electronics Engineers Inc., 2019 Conference on Lasers and Electro-Optics, CLEO 2019, San Jose, United States, 5 May 2019. https://doi.org/10.1364/cleo_qels.2019.ftu4c.4
Baxter, J., Lesina, A. C., Guay, J. M., Weck, A., Berini, P., & Ramunno, L. (2019). Application of deep learning to direct and inverse problems in plasmonic coloring. In 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings Article 8750346 (Conference on Lasers and Electro-Optics). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1364/cleo_qels.2019.ftu4c.4
Baxter J, Lesina AC, Guay JM, Weck A, Berini P, Ramunno L. Application of deep learning to direct and inverse problems in plasmonic coloring. In 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8750346. (Conference on Lasers and Electro-Optics). doi: 10.1364/cleo_qels.2019.ftu4c.4
Baxter, Josh ; Lesina, Antonino Cala ; Guay, Jean Michel et al. / Application of deep learning to direct and inverse problems in plasmonic coloring. 2019 Conference on Lasers and Electro-Optics, CLEO 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. (Conference on Lasers and Electro-Optics).
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title = "Application of deep learning to direct and inverse problems in plasmonic coloring",
abstract = "Laser pulses can color noble metals by inducing nanoparticles on their surface. We apply deep learning to solve the direct and inverse problems which link nanoparticle distributions and laser parameters to the produced colour.",
author = "Josh Baxter and Lesina, {Antonino Cala} and Guay, {Jean Michel} and Arnaud Weck and Pierre Berini and Lora Ramunno",
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