A spike-based few-shot framework with self-correlation and cross-correlation modules achieves 98.9% on N-Omniglot 5w5s and competitive ANN-level accuracy on CUB and miniImageNet.
Neural networks and back propagation algorithm
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Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning
A spike-based few-shot framework with self-correlation and cross-correlation modules achieves 98.9% on N-Omniglot 5w5s and competitive ANN-level accuracy on CUB and miniImageNet.