Multifunctional inverse sensing by spatial distribution characterization of scattering photons

Inverse sensing is an important research direction to provide new perspectives for optical sensing. For inverse sensing, the primary challenge is that scattered photon has a complicated profile, which is hard to derive a general solution. Instead of a general solution, it is more feasible and practi...

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Autores principales:	Chen Lianwei, Yin Yumeng, Li Yang, Hong Minghui
Formato:	article
Lenguaje:	EN
Publicado:	Institue of Optics and Electronics, Chinese Academy of Sciences 2019
Materias:	deep learning optical sensing photonics Optics. Light QC350-467
Acceso en línea:	https://doaj.org/article/e02e4be29abe4bf29cb7a7cea284ad66
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spelling	oai:doaj.org-article:e02e4be29abe4bf29cb7a7cea284ad662021-11-11T09:53:05ZMultifunctional inverse sensing by spatial distribution characterization of scattering photons2096-457910.29026/oea.2019.190019https://doaj.org/article/e02e4be29abe4bf29cb7a7cea284ad662019-09-01T00:00:00Zhttp://www.oejournal.org/article/doi/10.29026/oea.2019.190019https://doaj.org/toc/2096-4579Inverse sensing is an important research direction to provide new perspectives for optical sensing. For inverse sensing, the primary challenge is that scattered photon has a complicated profile, which is hard to derive a general solution. Instead of a general solution, it is more feasible and practical to derive a solution based on a specific environment. With deep learning, we develop a multifunctional inverse sensing approach for a specific environment. This inverse sensing approach can reconstruct the information of scattered photons and characterize multiple optical parameters simultaneously. Its functionality can be upgraded dynamically after learning more data. It has wide measurement range and can characterize the optical signals behind obstructions. The high anti-noise performance, flexible implementation, and extremely high threshold to optical damage or saturation make it useful for a wide range of applications, including self-driving car, space technology, data security, biological characterization, and integrated photonics.Chen LianweiYin YumengLi YangHong MinghuiInstitue of Optics and Electronics, Chinese Academy of Sciencesarticledeep learningoptical sensingphotonicsOptics. LightQC350-467ENOpto-Electronic Advances, Vol 2, Iss 9, Pp 190019-1-190019-8 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	deep learning optical sensing photonics Optics. Light QC350-467
spellingShingle	deep learning optical sensing photonics Optics. Light QC350-467 Chen Lianwei Yin Yumeng Li Yang Hong Minghui Multifunctional inverse sensing by spatial distribution characterization of scattering photons
description	Inverse sensing is an important research direction to provide new perspectives for optical sensing. For inverse sensing, the primary challenge is that scattered photon has a complicated profile, which is hard to derive a general solution. Instead of a general solution, it is more feasible and practical to derive a solution based on a specific environment. With deep learning, we develop a multifunctional inverse sensing approach for a specific environment. This inverse sensing approach can reconstruct the information of scattered photons and characterize multiple optical parameters simultaneously. Its functionality can be upgraded dynamically after learning more data. It has wide measurement range and can characterize the optical signals behind obstructions. The high anti-noise performance, flexible implementation, and extremely high threshold to optical damage or saturation make it useful for a wide range of applications, including self-driving car, space technology, data security, biological characterization, and integrated photonics.
format	article
author	Chen Lianwei Yin Yumeng Li Yang Hong Minghui
author_facet	Chen Lianwei Yin Yumeng Li Yang Hong Minghui
author_sort	Chen Lianwei
title	Multifunctional inverse sensing by spatial distribution characterization of scattering photons
title_short	Multifunctional inverse sensing by spatial distribution characterization of scattering photons
title_full	Multifunctional inverse sensing by spatial distribution characterization of scattering photons
title_fullStr	Multifunctional inverse sensing by spatial distribution characterization of scattering photons
title_full_unstemmed	Multifunctional inverse sensing by spatial distribution characterization of scattering photons
title_sort	multifunctional inverse sensing by spatial distribution characterization of scattering photons
publisher	Institue of Optics and Electronics, Chinese Academy of Sciences
publishDate	2019
url	https://doaj.org/article/e02e4be29abe4bf29cb7a7cea284ad66
work_keys_str_mv	AT chenlianwei multifunctionalinversesensingbyspatialdistributioncharacterizationofscatteringphotons AT yinyumeng multifunctionalinversesensingbyspatialdistributioncharacterizationofscatteringphotons AT liyang multifunctionalinversesensingbyspatialdistributioncharacterizationofscatteringphotons AT hongminghui multifunctionalinversesensingbyspatialdistributioncharacterizationofscatteringphotons
_version_	1718439266405580800

Multifunctional inverse sensing by spatial distribution characterization of scattering photons

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