English(EN) HAND: A Biologically-Inspired Activation Function that Improves Generalisation and Sample Efficiency in Image Classification

受生物启发的激活函数HAND可提高CNN泛化能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-09 04:00

研究人员开发了一种名为HAND（Homeostasis, Accelerating Nonlinearity, and Divisive-nomalisation）的新激活函数，其灵感来源于生物过程。该函数旨在提高卷积神经网络（CNN）在图像分类任务中的泛化能力和样本效率。实验表明，在ImageNet1k等数据集上使用HAND，可以显著减少ConvNeXt-tiny等模型的训练时间和数据需求，同时提高在长尾和损坏图像数据集上的准确性。 AI

影响这种新的激活函数有望提高图像分类模型的训练效率，降低计算成本和数据需求。

排序理由该集群包含一篇详细介绍改进AI模型新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Michael W. Spratling, Heiko H. Sch\"utt · 2026-10-09 04:00

HAND：一种受生物学启发的激活函数，可提高图像分类的泛化能力和样本效率

arXiv:2610.11534v1 Announce Type: cross Abstract: DNNs exhibit robustness and generalisation issues not seen in humans. They are also far less data-efficient learners, requiring considerably more training samples to accurately classify novel exemplars. Inductive bias could help w…

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HAND：一种受生物学启发的激活函数，可提高图像分类的泛化能力和样本效率

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