8 citations · 9 across the 8 of their papers we have counts for
8 papers
Spiking Neural Networks with Temporal Attention-Guided Adaptive Fusion for imbalanced Multi-modal Learning
Jiangrong Shen, Yulin Xie, Qi Xu +3
Multimodal spiking neural networks (SNNs) hold significant potential for energy-efficient sensory processing but face critical challenges in modality imbalance and temporal misalig…
Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning
Qi Xu, Junyang Zhu, Dongdong Zhou +4
Deep neural networks (DNNs) excel in computer vision tasks, especially, few-shot learning (FSL), which is increasingly important for generalizing from limited examples. However, DN…
Efficient ANN-SNN Conversion with Error Compensation Learning
Chang Liu, Jiangrong Shen, Xuming Ran +4
Artificial neural networks (ANNs) have demonstrated outstanding performance in numerous tasks, but deployment in resource-constrained environments remains a challenge due to their…
Hybrid Spiking Vision Transformer for Object Detection with Event Cameras
Qi Xu, Jie Deng, Jiangrong Shen +3
Event-based object detection has gained increasing attention due to its advantages such as high temporal resolution, wide dynamic range, and asynchronous address-event representati…
Improving the Sparse Structure Learning of Spiking Neural Networks from the View of Compression Efficiency
Jiangrong Shen, Qi Xu, Gang Pan +1
The human brain utilizes spikes for information transmission and dynamically reorganizes its network structure to boost energy efficiency and cognitive capabilities throughout its…
ALADE-SNN: Adaptive Logit Alignment in Dynamically Expandable Spiking Neural Networks for Class Incremental Learning
Wenyao Ni, Jiangrong Shen, Qi Xu +1
Inspired by the human brain's ability to adapt to new tasks without erasing prior knowledge, we develop spiking neural networks (SNNs) with dynamic structures for Class Incremental…
Context Gating in Spiking Neural Networks: Achieving Lifelong Learning through Integration of Local and Global Plasticity
Jiangrong Shen, Wenyao Ni, Qi Xu +2
Humans learn multiple tasks in succession with minimal mutual interference, through the context gating mechanism in the prefrontal cortex (PFC). The brain-inspired models of spikin…
Towards Efficient Deep Spiking Neural Networks Construction with Spiking Activity based Pruning
Yaxin Li, Qi Xu, Jiangrong Shen +3
The emergence of deep and large-scale spiking neural networks (SNNs) exhibiting high performance across diverse complex datasets has led to a need for compressing network models du…