TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networks

• Published in: IEEE transaction on neural networks and learning systems Vol. 36; no. 3; pp. 5112 - 5125
• Main Authors: Zhu, Rui-Jie, Zhang, Malu, Zhao, Qihang, Deng, Haoyu, Duan, Yule, Deng, Liang-Jian
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.03.2025
• Subjects: Attention mechanism; Biological neural networks; Biological system modeling; Correlation; neuromorphic datasets; Neurons; spatiotemporal information; Spatiotemporal phenomena; spiking neural networks (SNNs); Task analysis; Training

Spiking neural networks (SNNs) are attracting widespread interest due to their biological plausibility, energy efficiency, and powerful spatiotemporal information representation ability. Given the critical role of attention mechanisms in enhancing neural network performance, the integration of SNNs...