Live Demonstration: Handwritten Digit Recognition Using Spiking Deep Belief Networks on SpiNNaker.

Evangelos Stromatias, Daniel Neil, Francesco Galluppi, Michael Pfeiffer, Shih-Chii Liu and Steve Furber

Abstract

We demonstrate an interactive handwritten digit recognition system with a spike-based deep belief network running in real-time on SpiNNaker, a biologically inspired manycore architecture. Results show that during the simulation a SpiNNaker chip can deliver spikes in under 1 s, with a classification latency in the order of tens of milliseconds, while consuming less than 0.3 W