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This architecture reduces backend parameters by 55.16% while enhancing machine vision performance through tensor fusion and pooling.
We present a photonic network-in-network architecture integrating an on-chip diffractive optical neural network for parallel tensor fusion and channel-wise pooling, reducing back-end parameters by 55.16% while maintaining competitive performance in machine vision over benchmark datasets.
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Huang et al. (2025) studied this question.
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