Deep Spiking Neural Network for object tracking

Abstract

We are investigating surrogate gradient as optimization methods in Deep SNN for regression prob- lems. A SNN able to detect a ball at high speed is being developed in which the voltage potential of the output neurons correspond, in real time, with its position, making possible its application in robotic systems that require fast object tracking. As a future work, training and validation over the network and dataset design would be performed using PyTorch framework, as well as the deployment of the system into a robotic platform, for object identification and tracking.