Scene Context Classification with Event-Driven Spiking Deep Neural Networks

BERNABE LINARES-BARRANCO; SOTO, MIKEL; NEGRI, PABLO; TERESA SERRANO-GOTARREDONA

Bordeux

Congreso; 25th IEEE International Conference on Electronics, Circuits and Systems (ICECS); 2018

IEEE

Event-Driven computation is attracting growing attention among researchers for several reasons. On one hand, the availability of new bio-inspired retina-like vision sensors that provide spiking outputs, like the Dynamic Vision Sensor (DVS) make it possible to demonstrate energy efficient and high-speed complex vision tasks. On the other hand, the emergence of abundant new nanoscale devices that operate as tunable two-terminal resistive elements, which when operated through dynamic pulsing techniques emulate learning and processing in the brain, promise an explosion of highly compact energy efficient neuromorphic event-driven applications. In this paper we focus for the first time on a high-level cognitive task, namely scene context classification, performed by event-driven computations and using real sensory data from a DVS camera.