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20202026
most citedOptimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks

88 citations · 123 across the 22 of their papers we have counts for

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Showing 2023Show all

6 papers · 1 filter

cs.NE2023★ 3 cited

SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence

Wei Fang, Yanqi Chen, Jianhao Ding +7

Spiking neural networks (SNNs) aim to realize brain-inspired intelligence on neuromorphic chips with high energy efficiency by introducing neural dynamics and spike properties. As…

q-bio.NC2023

Spike timing reshapes robustness against attacks in spiking neural networks

Jianhao Ding, Zhaofei Yu, Tiejun Huang +1

The success of deep learning in the past decade is partially shrouded in the shadow of adversarial attacks. In contrast, the brain is far more robust at complex cognitive tasks. Ut…

cs.NE2023★ 88 cited

Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks

Tong Bu, Wei Fang, Jianhao Ding +3

Spiking Neural Networks (SNNs) have gained great attraction due to their distinctive properties of low power consumption and fast inference on neuromorphic hardware. As the most ef…

cs.CV2023★ 1 cited

SpikeCV: Open a Continuous Computer Vision Era

Yajing Zheng, Jiyuan Zhang, Rui Zhao +5

SpikeCV is a new open-source computer vision platform for the spike camera, which is a neuromorphic visual sensor that has developed rapidly in recent years. In the spike camera, e…

cs.NE2023★ 11 cited

Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes

Zecheng Hao, Jianhao Ding, Tong Bu +2

Spiking Neural Networks (SNNs) have attracted great attention due to their distinctive characteristics of low power consumption and temporal information processing. ANN-SNN convers…

cs.NE2023★ 2 cited

Reducing ANN-SNN Conversion Error through Residual Membrane Potential

Zecheng Hao, Tong Bu, Jianhao Ding +2

Spiking Neural Networks (SNNs) have received extensive academic attention due to the unique properties of low power consumption and high-speed computing on neuromorphic chips. Amon…