In this demonstration a spiking neural network
architecture for vision recognition using an FPGA spiking
convolution processor, based on leaky integrate and fire neurons
(LIF) and a SpiNNaker board is presented. The network has
been trained with Poker-DVS dataset in order to classify the
four different card symbols. The spiking convolution processor
extracts features from images in form of spikes, computes by
one layer of 64 convolutions. These features are sent to an
OKAERtool board that converts from AER to 2-7 protocol
to be classified by a spiking neural network deployed on a
SpiNNaker platform
