Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead
of capturing images at a fixed rate, they asynchronously measure per-pixel brightness …

Spiking neural networks (SNNs) are inspired by information processing in biology, where
sparse and asynchronous binary signals are communicated and processed in a massively …

Neuromorphic event-based image sensors capture only the dynamic motion in a scene,
which is then transferred to computation units for motion recognition. This approach …

With the advent of the Internet of Things era, the detection and recognition of moving objects
is becoming increasingly important. The current motion detection and recognition (MDR) …

Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …

Deep artificial neural networks apply principles of the brain's information processing that led
to breakthroughs in machine learning spanning many problem domains. Neuromorphic …

Neuro-inspired vision systems hold great promise to address the growing demands of mass
data processing for edge computing, a distributed framework that brings computation and …

Abstract Machine vision technology has taken huge leaps in recent years, and is now
becoming an integral part of various intelligent systems, including autonomous vehicles and …

To help meet the increasing need for dynamic vision sensor (DVS) event camera data, this
paper proposes the v2e toolbox that generates realistic synthetic DVS events from intensity …

Parallel perception of visual motion is of crucial significance to the development of an
intelligent machine vision system. However, implementing in-sensor parallel visual motion …