6 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…