Dr. Yi Xiong Profile

Dr. Yi Xiong

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Proceedings Article | 27 November 2023 Paper

Multilayer optoelectronic hybrid convolutional neural network with an optical 4f-system recurrent structure

Jie Chen, Huarong Gu, Hongwei Zhang, Jie Zhong, Yi Xiong

Proceedings Volume 12768, 1276810 (2023) https://doi.org/10.1117/12.2686844

KEYWORDS: Convolution, Point spread functions, Artificial neural networks, Optoelectronics, Spatial light modulators, Convolutional neural networks, Digital micromirror devices

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After decades of development, artificial neural network has become one of the most important research directions of artificial intelligence, and has a wide range of applications and important value in computer vision, natural language processing and other fields. Today, most of the applied artificial neural networks are based on von Neumann electronic hardware. As the semiconductor process approaches the physical limit, the performance growth encounters bottlenecks, and the power consumption problem is difficult to solve, limiting the application and further development of deep learning. Optical neural network provides a way to break through the bottleneck due to its high speed, high parallelism and low power consumption. At present, most optical neural networks are difficult to expand the depth of the network and have limited performance. In this paper, a multilayer optoelectronic hybrid convolutional neural network with an optical 4f-system recurrent structure is proposed. The electronic convolutional layer is replaced by an optical convolutional layer based on the 4f system, and the depth of the neural network is extended by the recurrent structure of the 4f system to improve its performance. Experiments show that the recognition accuracy of CIFAR-10 dataset of the proposed hybrid neural network is close to that of a corresponding electronic neural network. This work provides a possible way to build a deeper optoelectronic hybrid convolutional neural network when dealing with complicated problems.

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