TY - GEN
T1 - Classification of Energy Densities of Transmission Eigenchannels of Complex Photonic Media using Machine Learning
AU - Spotnitz, Matthew Emerson
AU - Pribisova, Abigail
AU - Sarma, Raktim
AU - Briscoe, Jayson
N1 - Publisher Copyright:
CLEO 2023 © Optica Publishing Group 2023, © 2023 The Author(s)
PY - 2023
Y1 - 2023
N2 - We demonstrate classification of energy densities of transmission eigenchannels and corresponding disorder strength of a single configuration of a complex medium using supervised machine learning techniques with an accuracy greater than 95 %.
AB - We demonstrate classification of energy densities of transmission eigenchannels and corresponding disorder strength of a single configuration of a complex medium using supervised machine learning techniques with an accuracy greater than 95 %.
UR - https://www.scopus.com/pages/publications/85191470094
U2 - 10.1364/CLEO_AT.2023.JTu2A.157
DO - 10.1364/CLEO_AT.2023.JTu2A.157
M3 - Conference contribution
AN - SCOPUS:85191470094
T3 - CLEO: Applications and Technology, CLEO:A and T 2023
BT - CLEO
PB - Optical Society of America
T2 - CLEO: Applications and Technology, CLEO:A and T 2023 - Part of Conference on Lasers and Electro-Optics 2023
Y2 - 7 May 2023 through 12 May 2023
ER -