English(EN) 16-bit Precision of Convolutional Neural Networks on Microcontroller Units for 8-bit Costs

新的W16A16量化方法提高了MCUs上CNN的准确性

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-05 04:00

研究人员开发了一种名为W16A16的新型量化方法，用于在微控制器单元（MCUs）上部署深度神经网络。这种16位精度的方法与8位方法相比，显著减少了量化误差，误差降低了约10倍，同时保持或提高了推理速度和能耗。该方法已在Armv7E-M架构上进行了评估，证明了其在高效边缘硬件部署方面的有效性。 AI

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arXiv cs.LG TIER_1 English(EN) · Rui Liu, Benjamin Paa{\ss}en · 2026-10-05 04:00

用于8位成本的微控制器单元上的卷积神经网络的16位精度

arXiv:2610.03402v1 Announce Type: new Abstract: To deploy deep neural networks on edge hardware, highly efficient inference schemes are necessary that retain high accuracy. This work presents W16A16, a high precision (16-bit), fast speed, low energy quantization method. On a wide…