Benoît Miramond

A Hardware-Aware Analysis of Energy Efficiency and Quantization Trade-Offs in Spiking Neural Networks

An in depth analysis of the different trade-offs between quantization, generalization performance, and energy efficiency between binary SNNs, multi-level SNNs and ANNs for two different applications scenarios: image classification and image denoising and results show that multi-level spiking neurons provide better information compression, allowing therefore a reduction in latency without performance loss for classification tasks.