Photonic Max-Pooling for Deep Neural Networks Using a Programmable Photonic Platform

Farshid Ashtiani,Mehmet Berkay On, David Sanchez-Jacome, Daniel Perez-Lopez, S. J. Ben Yoo, Andrea Blanco-Redondo

2023 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXHIBITION, OFC（2023）

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Abstract

We propose a photonic max-pooling architecture for photonic neural networks which is compatible with integrated photonic platforms. As a proof of concept, we have experimentally demonstrated the max-pooling function on a programmable photonic platform consisting of a hexagonal mesh of Mach-Zehnder interferometers. (C) 2022 The Author(s)

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