https://doi.org/10.1051/epjconf/202328713013
Image classification with a fully connected opto-electronic neural network
1 Max Planck Institute for Medical Research, Jahnstraße 29, 69120 Heidelberg
2 Institute for Molecular Systems Engineering and Advanced Materials, Universität Heidelberg, Neuenheimer Feld 225, 69120 Heidel-berg
† Equal Contribution
* e-mail: alexander.song@mr.mpg.de
** e-mail: nikhilesh.kottapalli@mr.mpg.de
*** e-mail: peer.fischer@mr.mpg.de
Published online: 18 October 2023
Optical approaches have made great strides enabling high-speed, scalable computing necessary for modern deep learning and AI applications. In this study, we introduce a multilayer optoelectronic computing framework that alternates between optical and optoelectronic layers to implement matrix-vector multiplications and rectified linear functions, respectively. The system is designed to be real-time and parallelized, utilizing arrays of light emitters and detectors connected with independent analog electronics. We experimentally demonstrate the operation of our system and compare its performance to a single-layer analog through simulations.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
