Diffractive optical neural networks

Aydogan Ozcan

doi:10.1117/12.2585708

5 March 2021 Diffractive optical neural networks

Aydogan Ozcan

Proceedings Volume 11703, AI and Optical Data Sciences II; 117030G (2021) https://doi.org/10.1117/12.2585708
Event: SPIE OPTO, 2021, Online Only

Abstract

We introduce a diffractive optical neural network architecture that can all-optically implement various functions, following the deep learning-based design of passive layers that work collectively. We created 3D-printed diffractive networks that implement all-optical classification of images of handwritten digits and fashion products as well as the function of an imaging lens, spectral filters, wavelength demultiplexers and ultra-short pulse shapers at terahertz part of the spectrum. This passive diffractive network framework is broadly applicable to different parts of the electromagnetic spectrum, including the visible wavelengths, and can perform at the speed of light various complex functions that computer-based neural networks can implement, and will find applications in all-optical image analysis, feature detection and object classification, also enabling new camera designs and optical components that perform unique tasks using diffractive networks designed by deep learning.

Conference Presentation

Citation Download Citation

Aydogan Ozcan "Diffractive optical neural networks", Proc. SPIE 11703, AI and Optical Data Sciences II, 117030G (5 March 2021); https://doi.org/10.1117/12.2585708

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