Reliable Object Tracking by Multimodal Hybrid Feature Extraction and Transformer-Based Fusion

no code implementations • 28 May 2024 • Hongze Sun, Rui Liu, Wuque Cai, Jun Wang, Yue Wang, Huajin Tang, Yan Cui, Dezhong Yao, Daqing Guo

In this study, we propose a novel multimodal hybrid tracker (MMHT) that utilizes frame-event-based data for reliable single object tracking.

A Spatial-channel-temporal-fused Attention for Spiking Neural Networks

no code implementations • 22 Sep 2022 • Wuque Cai, Hongze Sun, Rui Liu, Yan Cui, Jun Wang, Yang Xia, Dezhong Yao, Daqing Guo

Spiking neural networks (SNNs) mimic brain computational strategies, and exhibit substantial capabilities in spatiotemporal information processing.

A Synapse-Threshold Synergistic Learning Approach for Spiking Neural Networks

1 code implementation • 10 Jun 2022 • Hongze Sun, Wuque Cai, Baoxin Yang, Yan Cui, Yang Xia, Dezhong Yao, Daqing Guo

Most existing methods for training SNNs are based on the concept of synaptic plasticity; however, learning in the realistic brain also utilizes intrinsic non-synaptic mechanisms of neurons.

Event data classification Gesture Recognition +1