Details
| Original language | English |
|---|---|
| Title of host publication | 2018 Photonics North, PN 2018 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (print) | 9781538675212 |
| Publication status | Published - Aug 2018 |
| Externally published | Yes |
| Event | 2018 Photonics North, PN 2018 - Montreal, Canada Duration: 5 Jun 2018 → 7 Jun 2018 |
Abstract
The abundance of acquired data from experiments and simulations makes the field of photonics a perfect environment for machine learning applications. Here we will apply Deep Neural Networks (DNNs) to predict the colour of nano-structured surfaces using either the nanoparticle geometric parameters, or laser parameters used to develop the nano-structured surfaces.
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
- Physics and Astronomy(all)
- Atomic and Molecular Physics, and Optics
- Materials Science(all)
- Electronic, Optical and Magnetic Materials
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2018 Photonics North, PN 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8438845.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Machine Learning Applications in Plasmonics
AU - Baxter, J.
AU - Lesina, A. Cala
AU - Guay, J. M.
AU - Ramunno, L.
PY - 2018/8
Y1 - 2018/8
N2 - The abundance of acquired data from experiments and simulations makes the field of photonics a perfect environment for machine learning applications. Here we will apply Deep Neural Networks (DNNs) to predict the colour of nano-structured surfaces using either the nanoparticle geometric parameters, or laser parameters used to develop the nano-structured surfaces.
AB - The abundance of acquired data from experiments and simulations makes the field of photonics a perfect environment for machine learning applications. Here we will apply Deep Neural Networks (DNNs) to predict the colour of nano-structured surfaces using either the nanoparticle geometric parameters, or laser parameters used to develop the nano-structured surfaces.
UR - http://www.scopus.com/inward/record.url?scp=85053129528&partnerID=8YFLogxK
U2 - 10.1109/pn.2018.8438845
DO - 10.1109/pn.2018.8438845
M3 - Conference contribution
AN - SCOPUS:85053129528
SN - 9781538675212
BT - 2018 Photonics North, PN 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Photonics North, PN 2018
Y2 - 5 June 2018 through 7 June 2018
ER -