Publication

Learning to See and Compute through Multimode Fibers

Demetri Psaltis, Christophe Moser, Damien Claude-Marie Loterie, Eirini Kakkava, Navid Borhani, Babak Rahmani, Ilker Oguz, Ugur Tegin, Mustafa Yildirim
2021
Conference Papers

Abstract

We propose a computational method for controlling the output of a multimode fiber using machine learning. Arbitrary images can be projected with amplitude-only calibration (no phase measurement) and fidelities on par with conventional full-measurement methods. We also show the reverse, meaning that multimode fibers can be used as a computational tool that harnesses spatiotemporal nonlinear effects to perform end to end learning tasks with unprecedented speed and low power consumption.

Official source

https://infoscience.epfl.ch/entities/publication/d0c8d92c-5acf-4c38-bbca-8f79ed307beb

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Learning to See and Compute through Multimode Fibers

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