Dynamic Vision Sensor (DVS) event camera output includes uninformative background
activity (BA) noise events that increase dramatically under dim lighting. Existing denoising …

Evolution has honed predatory skills in the natural world where localizing and intercepting
fast-moving prey is required. The current generation of robotic systems mimics these …

Neuromorphic vision sensors (NVSs) can enable energy savings due to their event-driven
that exploits the temporal redundancy in video streams from a stationary camera. However …

Neuromorphic vision sensors (NVSs) are key enablers of energy savings in Internet of
Things (IoT)-based traffic monitoring and surveillance systems that exploit the temporal …

In contrast to conventional vision sensors that produce images of the entire field-of-view at a
fixed frame rate, dynamic vision sensors (DVS) are neuromorphic devices that only produce …

Neuromorphic vision sensors (NVSs) save energy and reduce data at the source by
asynchronously recording changes in temporal contrast. Thus, NVS provides an opportunity …

Deep learning inference that needs to largely take place on the “edge” is a highly
computational and memory intensive workload, making it intractable for low-power …

We introduce the single-shot optical flow estimation algorithm (SOFEA) to non-iteratively
compute the continuous-time flow information of events produced from bio-inspired cameras …

In this paper, we review recent work published over the last 3 years under the umbrella of
Neuromorphic engineering to analyze what are the common features among such systems …

Although advances in event-based machine vision algorithms have demonstrated
unparalleled capabilities in performing some of the most demanding tasks, their …