21 citations · 26 across the 4 of their papers we have counts for
5 papers
Towards Efficient Processing and Learning with Spikes: New Approaches for Multi-Spike Learning
Qiang Yu, Shenglan Li, Huajin Tang +3
Spikes are the currency in central nervous systems for information transmission and processing. They are also believed to play an essential role in low-power consumption of the bio…
Effective AER Object Classification Using Segmented Probability-Maximization Learning in Spiking Neural Networks
Qianhui Liu, Haibo Ruan, Dong Xing +2
Address event representation (AER) cameras have recently attracted more attention due to the advantages of high temporal resolution and low power consumption, compared with traditi…
Unsupervised AER Object Recognition Based on Multiscale Spatio-Temporal Features and Spiking Neurons
Qianhui Liu, Gang Pan, Haibo Ruan +3
This paper proposes an unsupervised address event representation (AER) object recognition approach. The proposed approach consists of a novel multiscale spatio-temporal feature (Mu…
Robust Environmental Sound Recognition with Sparse Key-point Encoding and Efficient Multi-spike Learning
Qiang Yu, Yanli Yao, Longbiao Wang +3
The capability for environmental sound recognition (ESR) can determine the fitness of individuals in a way to avoid dangers or pursue opportunities when critical sound events occur…
Spiking Deep Residual Network
Yangfan Hu, Huajin Tang, Gang Pan
Spiking neural networks (SNNs) have received significant attention for their biological plausibility. SNNs theoretically have at least the same computational power as traditional a…