Abstract

The parallelism of optics and the miniaturization of optical components using nanophotonic structures, such as metasurfaces, present a compelling alternative to electronic implementations of convolutional neural networks. The lack of a low-power optical nonlinearity, however, requires slow and energy-inefficient conversions between the electronic and optical domains. Here, we design an architecture that utilizes a single electrical to optical conversion by designing a free-space optical frontend unit that implements the linear operations of the first layer with the subsequent layers realized electronically. Speed and power analysis of the architecture indicates that the hybrid photonic–electronic architecture outperforms a fully electronic architecture for large image sizes and kernels. Benchmarking of the photonic–electronic architecture on a modified version of AlexNet achieves high classification accuracies on images from the Kaggle’s Cats and Dogs challenge and MNIST databases.

© 2019 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
High-accuracy optical convolution unit architecture for convolutional neural networks by cascaded acousto-optical modulator arrays

Shaofu Xu, Jing Wang, Rui Wang, Jiangping Chen, and Weiwen Zou
Opt. Express 27(14) 19778-19787 (2019)

Segmentation of mouse skin layers in optical coherence tomography image data using deep convolutional neural networks

Timo Kepp, Christine Droigk, Malte Casper, Michael Evers, Gereon Hüttmann, Nunciada Salma, Dieter Manstein, Mattias P. Heinrich, and Heinz Handels
Biomed. Opt. Express 10(7) 3484-3496 (2019)

Deblurring adaptive optics retinal images using deep convolutional neural networks

Xiao Fei, Junlei Zhao, Haoxin Zhao, Dai Yun, and Yudong Zhang
Biomed. Opt. Express 8(12) 5675-5687 (2017)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (3)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Tables (3)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (3)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Metrics

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription