Biology provides examples of efficient machines which greatly outperform conventional
technology. Designers in neuromorphic engineering aim to construct electronic systems with …

The four chips presented in the special session on" Activity-driven, event-based vision
sensors" quickly output compressed digital data in the form of events. These sensors reduce …

Today's autonomous drones have reaction times of tens of milliseconds, which is not
enough for navigating fast in complex dynamic environments. To safely avoid fast moving …

Neuromorphic data, recording frameless spike events, have attracted considerable attention
for the spatiotemporal information components and the event-driven processing fashion …

Conventional vision-based robotic systems that must operate quickly require high video
frame rates and consequently high computational costs. Visual response latencies are lower …

Spatio-temporal pattern recognition is a fundamental ability of the brain which is required for
numerous real-world activities. Recent deep learning approaches have reached outstanding …

We present the D-eDVS-a combined event-based 3D sensor—and a novel event-based full-
3D simultaneous localization and map** algorithm which works exclusively with the …

This paper presents a new high speed vision system using an asynchronous address‐event
representation camera. Within this framework, an asynchronous event‐based real‐time …

The nervous systems converts the physical quantities sensed by its primary receptors into
trains of events that are then processed in the brain. The unmatched efficiency in information …

This paper presents a long-term object tracking framework with a moving event camera
under general tracking conditions. A first of its kind for these revolutionary cameras, the …