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17 March 2023 Image sensing with multilayer nonlinear optical neural networks
Tianyu Wang, Mandar M. Sohoni, Logan G. Wright, Tatsuhiro Onodera, Shi-Yuan Ma, Maxwell Anderson, Peter L. McMahon
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Proceedings Volume PC12438, AI and Optical Data Sciences IV; PC124380M (2023) https://doi.org/10.1117/12.2650289
Event: SPIE OPTO, 2023, San Francisco, California, United States
Abstract
Linear optics has been long applied to image compression. However, it is widely known that nonlinear neural networks outperform linear models in terms of feature extraction and image compression. Here, we show a nonlinear multilayer optical neural network using a commercially available image intensifier as a scalable optical-to-optical nonlinear activation function. We experimentally demonstrated that nonlinear ONNs outperform linear optical linear encoders in a variety of non-trivial machine vision tasks at a high image compression ratio (up to 800:1). We have shown that nonlinear ONNs can directly process optical inputs from physical objects under natural illumination, which provides a new pathway towards high-volume, high-throughput, and low-latency machine vision processing.
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Tianyu Wang, Mandar M. Sohoni, Logan G. Wright, Tatsuhiro Onodera, Shi-Yuan Ma, Maxwell Anderson, and Peter L. McMahon "Image sensing with multilayer nonlinear optical neural networks", Proc. SPIE PC12438, AI and Optical Data Sciences IV, PC124380M (17 March 2023); https://doi.org/10.1117/12.2650289
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KEYWORDS
Neural networks
Nonlinear optics
Computer programming
Image compression
Machine vision
Image classification
Image sensors
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