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arXiv · 2308.03321

AFN: Adaptive Fusion Normalization via an Encoder-Decoder Framework

Zikai Zhou·Shuo Zhang·Ziruo Wang·Huanran Chen
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Abstract

The success of deep learning is inseparable from normalization layers. Researchers have proposed various normalization functions, and each of them has both advantages and disadvantages. In response, efforts have been made to design a unified normalization function that combines all normalization procedures and mitigates their weaknesses. We also proposed a new normalization function called Adaptive Fusion Normalization. Through experiments, we demonstrate AFN outperforms the previous normalization techniques in domain generalization and image classification tasks.

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Zikai Zhou, Shuo Zhang, Ziruo Wang, Huanran Chen. 2023-08-07. AFN: Adaptive Fusion Normalization via an Encoder-Decoder Framework. https://arxiv.org/abs/2308.03321

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