Integration of diffractive optical neural networks with electronic neural networks (Conference Presentation)

Aydogan Ozcan; Deniz Mengu; Yi Luo; Yair Rivenson; Jingxi Li

doi:10.1117/12.2547200

9 March 2020 Integration of diffractive optical neural networks with electronic neural networks (Conference Presentation)

Aydogan Ozcan, Deniz Mengu, Yi Luo, Yair Rivenson, Jingxi Li

Author Affiliations +

Proceedings Volume 11284, Smart Photonic and Optoelectronic Integrated Circuits XXII; 112841X (2020) https://doi.org/10.1117/12.2547200
Event: SPIE OPTO, 2020, San Francisco, California, United States

Abstract

We demonstrate significant improvements in the inference accuracy of diffractive optical neural networks and report that a five-layer, phase-only (or amplitude/phase) modulation diffractive network can achieve 97.18% (97.81%) and 89.13% (89.32%) blind-testing accuracy for MNIST and Fashion-MNIST datasets, respectively. Moreover, the integration of diffractive neural networks with electronic deep neural networks is investigated. Using a single fully-connected layer on the electronic part and a five-layer, phase-only diffractive neural network at the optical front-end, we achieved blind-testing accuracies of 98.71% and 90.04% for MNIST and Fashion-MNIST datasets, respectively, despite a >7.8-fold reduction in the number of pixels at the opto-electronic sensor-array.

Conference Presentation

Citation Download Citation

Aydogan Ozcan, Deniz Mengu, Yi Luo, Yair Rivenson, and Jingxi Li "Integration of diffractive optical neural networks with electronic neural networks (Conference Presentation)", Proc. SPIE 11284, Smart Photonic and Optoelectronic Integrated Circuits XXII, 112841X (9 March 2020); https://doi.org/10.1117/12.2547200

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