3 papers
cs.LG2025
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…
cs.CV2025
Temporal Separation with Entropy Regularization for Knowledge Distillation in Spiking Neural Networks
Kairong Yu, Chengting Yu, Tianqing Zhang +5
Spiking Neural Networks (SNNs), inspired by the human brain, offer significant computational efficiency through discrete spike-based information transfer. Despite their potential t…
cs.CV2025
STAA-SNN: Spatial-Temporal Attention Aggregator for Spiking Neural Networks
Tianqing Zhang, Kairong Yu, Xian Zhong +3
Spiking Neural Networks (SNNs) have gained significant attention due to their biological plausibility and energy efficiency, making them promising alternatives to Artificial Neural…