Search Results for author:
Found 4 papers, 1 papers with code
Reliable Object Tracking by Multimodal Hybrid Feature Extraction and Transformer-Based Fusion
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
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
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.
Time irreversibility and amplitude irreversibility measures for nonequilibrium processes
Time irreversibility should be measured based on the permutations of symmetric vectors rather than symmetric permutations, whereas symmetric permutations can instead be employed to determine the quantitative amplitude irreversibility -- a novel parameter proposed in this paper for nonequilibrium calculated by means of the probabilistic difference in amplitude fluctuations.
