most citedImproving Stability and Performance of Spiking Neural Networks through Enhancing Temporal Consistency

2 citations · 2 across the 1 of their papers we have counts for

collaborators

5 papers

cs.NE2023

Learning the Plasticity: Plasticity-Driven Learning Framework in Spiking Neural Networks

Guobin Shen, Dongcheng Zhao, Yiting Dong +3

The evolution of the human brain has led to the development of complex synaptic plasticity, enabling dynamic adaptation to a constantly evolving world. This progress inspires our e…

cs.CV2023

Bullying10K: A Large-Scale Neuromorphic Dataset towards Privacy-Preserving Bullying Recognition

Yiting Dong, Yang Li, Dongcheng Zhao +2

The prevalence of violence in daily life poses significant threats to individuals' physical and mental well-being. Using surveillance cameras in public spaces has proven effective…

cs.NE20232 cited

Improving Stability and Performance of Spiking Neural Networks through Enhancing Temporal Consistency

Dongcheng Zhao, Guobin Shen, Yiting Dong +2

Spiking neural networks have gained significant attention due to their brain-like information processing capabilities. The use of surrogate gradients has made it possible to train…

cs.NE2023

Dive into the Power of Neuronal Heterogeneity

Guobin Shen, Dongcheng Zhao, Yiting Dong +2

The biological neural network is a vast and diverse structure with high neural heterogeneity. Conventional Artificial Neural Networks (ANNs) primarily focus on modifying the weight…

cs.NE2023

Temporal Knowledge Sharing enable Spiking Neural Network Learning from Past and Future

Yiting Dong, Dongcheng Zhao, Yi Zeng

Spiking Neural Networks (SNNs) have attracted significant attention from researchers across various domains due to their brain-like information processing mechanism. However, SNNs…