Corpus ID: 236428732

Temporal-wise Attention Spiking Neural Networks for Event Streams Classification

@article{Yao2021TemporalwiseAS,
  title={Temporal-wise Attention Spiking Neural Networks for Event Streams Classification},
  author={Man Yao and Huanhuan Gao and Guangshe Zhao and Dingheng Wang and Yihan Lin and Zhaoxu Yang and Guoqi Li},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.11711}
}
  • Man Yao, Huanhuan Gao, +4 authors Guoqi Li
  • Published 2021
  • Computer Science
  • ArXiv
How to effectively and efficiently deal with spatiotemporal event streams, where the events are generally sparse and non-uniform and have the μs temporal resolution, is of great value and has various real-life applications. Spiking neural network (SNN), as one of the brain-inspired event-triggered computing models, has the potential to extract effective spatio-temporal features from the event streams. However, when aggregating individual events into frames with a new higher temporal resolution… Expand

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