Keys to Accurate Feature Extraction Using Residual Spiking Neural Networks. (arXiv:2111.05955v4 [cs.LG] UPDATED)

Spiking neural networks (SNNs) have become an interesting alternative to
conventional artificial neural networks (ANN) thanks to their temporal
processing capabilities and energy efficient implementations in neuromorphic
hardware. However the challenges involved in training SNNs have limited their
performance in terms of accuracy and thus their applications. Improving
learning algorithms and neural architectures for a more accurate feature
extraction is therefore one of the current priorities in SNN research. In this
paper we present a study on the key components …

arxiv extraction feature lg networks neural networks spiking neural networks