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  • Received: Jun. 10, 2019

    Accepted: Aug. 29, 2019

    Posted: Nov. 20, 2019

    Published Online: Nov. 20, 2019

    The Author Email: Hong Minghui (

    DOI: 10.29026/oea.2019.190019

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    Lianwei Chen, Yumeng Yin, Yang Li, Minghui Hong. Multifunctional inverse sensing by spatial distribution characterization of scattering photons[J]. Opto-Electronic Advances, 2019, 2(9): 190019-1

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Opto-Electronic Advances, Vol. 2, Issue 9, 190019-1 (2019)

Multifunctional inverse sensing by spatial distribution characterization of scattering photons

Lianwei Chen1, Yumeng Yin2, Yang Li1, and Minghui Hong1,*

Author Affiliations

  • 1Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117576, Singapore
  • 2Department of Computer Science, School of Computing, National University of Singapore, 117576, Singapore


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.


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