3 citations · 5 across the 5 of their papers we have counts for
4 papers · 1 filter
SDSNN: A Single-Timestep Spiking Neural Network with Self-Dropping Neuron and Bayesian Optimization
Changqing Xu, Buxuan Song, Yi Liu +3
Spiking Neural Networks (SNNs), as an emerging biologically inspired computational model, demonstrate significant energy efficiency advantages due to their event-driven information…
STCSNN: High energy efficiency spike-train level spiking neural networks with spatio-temporal conversion
Changqing Xu, Yi Liu, Yintang Yang
Brain-inspired spiking neuron networks (SNNs) have attracted widespread research interest due to their low power features, high biological plausibility, and strong spatiotemporal i…
Ultra-low Latency Adaptive Local Binary Spiking Neural Network with Accuracy Loss Estimator
Changqing Xu, Yijian Pei, Zili Wu +2
Spiking neural network (SNN) is a brain-inspired model which has more spatio-temporal information processing capacity and computational energy efficiency. However, with the increas…
Ultra-low Latency Spiking Neural Networks with Spatio-Temporal Compression and Synaptic Convolutional Block
Changqing Xu, Yi Liu, Yintang Yang
Spiking neural networks (SNNs), as one of the brain-inspired models, has spatio-temporal information processing capability, low power feature, and high biological plausibility. The…