Randomly Disordered Glass-Air Optical Fiber Imaging Based On Deep Learning

Abstract

We demonstrate that images can be reconstructed for objects away from the imaging plane without any distal optics by combining deep neural networks with meter-long glass-air disordered optical fibers. This imaging system is bending-independent.

Publication Date

1-1-2018

Publication Title

Optics InfoBase Conference Papers

Volume

Part F111-SOF 2018

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1364/SOF.2018.SoW1H.2

Socpus ID

85051258540 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85051258540

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