English(EN) Efficient EEG Seizure Detection Using INT8 Quantization, Channel Pruning, and Spiking Neural Networks

通过量化和剪枝提高脑电图癫痫检测模型的效率

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-21 04:00

研究人员开发了使深度神经网络更有效地从脑电图数据中检测癫痫发作的方法。他们探索了将卷积神经网络（CNN）转换为脉冲神经网络、剪枝脑电图通道以及使用INT8量化。这些技术将模型大小减少了高达73%，并将推理速度提高了2.8倍，同时保持或略微提高了癫痫检测的曲线下面积（AUC）。 AI

影响这些效率技术可以使资源受限的可穿戴设备上实现更复杂的AI驱动的癫痫检测。

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arXiv cs.AI TIER_1 English(EN) · Kartikey Ahlawat · 2026-07-21 04:00

利用INT8量化、通道剪枝和脉冲神经网络实现高效脑电图癫痫检测

arXiv:2607.16296v1 Announce Type: cross Abstract: Continuous EEG monitoring for epilepsy is constrained by the limited power and memory budgets of wearable and implantable devices. Deep neural networks can detect seizures with high accuracy, but their computational cost and model…