Neural network classification for intensity imaging through multimode optical fibres

Piergiorgio Caramazza; Roderick Murray-Smith; Daniele Faccio

doi:10.1364/COSI.2018.CW3B.4

Neural network classification for intensity imaging through multimode optical fibres

Piergiorgio Caramazza^*, Roderick Murray-Smith, Daniele Faccio

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A neural network algorithm is employed to successfully classify with intensityonly measurements, gray-scale hand-written digits propagated through a multimode fibre, promising an efficient approach for imaging through fibres.

Original language	English
Title of host publication	Computational Optical Sensing and Imaging 2018
Publisher	OSA Publishing
ISBN (Electronic)	9781943580446
DOIs	https://doi.org/10.1364/COSI.2018.CW3B.4
Publication status	Published - 2018

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Mechanics of Materials

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10.1364/COSI.2018.CW3B.4

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@inproceedings{0feed8917ace45a4b092934778307054,

title = "Neural network classification for intensity imaging through multimode optical fibres",

abstract = "A neural network algorithm is employed to successfully classify with intensityonly measurements, gray-scale hand-written digits propagated through a multimode fibre, promising an efficient approach for imaging through fibres.",

author = "Piergiorgio Caramazza and Roderick Murray-Smith and Daniele Faccio",

year = "2018",

doi = "10.1364/COSI.2018.CW3B.4",

language = "English",

booktitle = "Computational Optical Sensing and Imaging 2018",

publisher = "OSA Publishing",

address = "United States",

}

TY - GEN

T1 - Neural network classification for intensity imaging through multimode optical fibres

AU - Caramazza, Piergiorgio

AU - Murray-Smith, Roderick

AU - Faccio, Daniele

PY - 2018

Y1 - 2018

N2 - A neural network algorithm is employed to successfully classify with intensityonly measurements, gray-scale hand-written digits propagated through a multimode fibre, promising an efficient approach for imaging through fibres.

AB - A neural network algorithm is employed to successfully classify with intensityonly measurements, gray-scale hand-written digits propagated through a multimode fibre, promising an efficient approach for imaging through fibres.

UR - https://www.scopus.com/pages/publications/85051264445

U2 - 10.1364/COSI.2018.CW3B.4

DO - 10.1364/COSI.2018.CW3B.4

M3 - Conference contribution

AN - SCOPUS:85051264445

BT - Computational Optical Sensing and Imaging 2018

PB - OSA Publishing

ER -

Neural network classification for intensity imaging through multimode optical fibres

Abstract

ASJC Scopus subject areas

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