Superresolution of three point-sources assisted with machine learning

Bilal Benzimoun; Abdelali Sajia; Xiao Feng Qian

Superresolution of three point-sources assisted with machine learning

Bilal Benzimoun, Abdelali Sajia, Xiao Feng Qian

Department of Physics

Research output: Contribution to conference › Paper › peer-review

Abstract

We demonstrate super-resolved localization of three point sources with the assistance of a machine learning model that is based on the decomposition of the source signal into Hermite Gaussian modes. High fidelity of over 80% is achieved.

Original language	English
State	Published - 2024
Event	2024 Frontiers in Optics, FiO 2024 - Denver, United States Duration: 23 Sep 2024 → 26 Sep 2024

Conference

Conference	2024 Frontiers in Optics, FiO 2024
Country/Territory	United States
City	Denver
Period	23/09/24 → 26/09/24

Cite this

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title = "Superresolution of three point-sources assisted with machine learning",

abstract = "We demonstrate super-resolved localization of three point sources with the assistance of a machine learning model that is based on the decomposition of the source signal into Hermite Gaussian modes. High fidelity of over 80% is achieved.",

author = "Bilal Benzimoun and Abdelali Sajia and Qian, {Xiao Feng}",

note = "Publisher Copyright: {\textcopyright} Optica Publishing Group 2024, {\textcopyright} 2024 The Author(s); 2024 Frontiers in Optics, FiO 2024 ; Conference date: 23-09-2024 Through 26-09-2024",

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language = "English",

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TY - CONF

T1 - Superresolution of three point-sources assisted with machine learning

AU - Benzimoun, Bilal

AU - Sajia, Abdelali

AU - Qian, Xiao Feng

PY - 2024

Y1 - 2024

N2 - We demonstrate super-resolved localization of three point sources with the assistance of a machine learning model that is based on the decomposition of the source signal into Hermite Gaussian modes. High fidelity of over 80% is achieved.

AB - We demonstrate super-resolved localization of three point sources with the assistance of a machine learning model that is based on the decomposition of the source signal into Hermite Gaussian modes. High fidelity of over 80% is achieved.

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M3 - Paper

AN - SCOPUS:85216090813

T2 - 2024 Frontiers in Optics, FiO 2024

Y2 - 23 September 2024 through 26 September 2024

ER -

Superresolution of three point-sources assisted with machine learning

Abstract

Conference

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