Yongbiao Chen — accepted AI-conference papers

2022

DynSNN: A Dynamic Approach to Reduce Redundancy in Spiking Neural Networks

Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Fei Dai

ICASSP 2022accepted

Current Internet of Things (IoT) embedded applications use machine learning algorithms to process the collected data. However, the computational complexity and storage requirements of existing deep learning methods hinder the wide availability of embedded applications. Spiking Neural Networks (SNN)…

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2022

SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks

Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Li Jiang

AAAI 2022technical

Spiking Neural Networks (SNNs) have recently attracted enormous research interest since their event-driven and brain-inspired structure enables low-power computation. In image recognition tasks, the best results are achieved by SNN so far utilizing ANN-SNN conversion methods that replace activation…

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