18 citations · 21 across the 8 of their papers we have counts for
8 papers
Reconstructing Spiking Neural Networks Using a Single Neuron with Autapses
Wuque Cai, Hongze Sun, Quan Tang +6
Spiking neural networks (SNNs) are promising for neuromorphic computing, but high-performing models still rely on dense multilayer architectures with substantial communication and…
NSPDI-SNN: An efficient lightweight SNN based on nonlinear synaptic pruning and dendritic integration
Wuque Cai, Hongze Sun, Jiayi He +5
Spiking neural networks (SNNs) are artificial neural networks based on simulated biological neurons and have attracted much attention in recent artificial intelligence technology s…
Toward Efficient Spiking Transformers: Synapse Pruning Meets Synergistic Learning-Based Compensation
Hongze Sun, Wuque Cai, Duo Chen +7
As a foundational architecture of artificial intelligence models, Transformer has been recently adapted to spiking neural networks with promising performance across various tasks.…
A Brain-to-Population Graph Learning Framework for Diagnosing Brain Disorders
Qianqian Liao, Wuque Cai, Hongze Sun +4
Recent developed graph-based methods for diagnosing brain disorders using functional connectivity highly rely on predefined brain atlases, but overlook the rich information embedde…
ST-FlowNet: An Efficient Spiking Neural Network for Event-Based Optical Flow Estimation
Hongze Sun, Jun Wang, Wuque Cai +6
Spiking Neural Networks (SNNs) have emerged as a promising tool for event-based optical flow estimation tasks due to their ability to leverage spatio-temporal information and low-p…
Reliable Object Tracking by Multimodal Hybrid Feature Extraction and Transformer-Based Fusion
Hongze Sun, Rui Liu, Wuque Cai +6
Visual object tracking, which is primarily based on visible light image sequences, encounters numerous challenges in complicated scenarios, such as low light conditions, high dynam…
A Spatial-channel-temporal-fused Attention for Spiking Neural Networks
Wuque Cai, Hongze Sun, Rui Liu +5
Spiking neural networks (SNNs) mimic brain computational strategies, and exhibit substantial capabilities in spatiotemporal information processing. As an essential factor for human…
A Synapse-Threshold Synergistic Learning Approach for Spiking Neural Networks
Hongze Sun, Wuque Cai, Baoxin Yang +4
Spiking neural networks (SNNs) have demonstrated excellent capabilities in various intelligent scenarios. Most existing methods for training SNNs are based on the concept of synapt…