Guided by brain-like 'spiking'computational frameworks, neuromorphic computing—brain-
inspired computing for machine intelligence—promises to realize artificial intelligence while …

The design of robots that interact autonomously with the environment and exhibit complex
behaviours is an open challenge that can benefit from understanding what makes living …

The best performing learning algorithms devised for event cameras work by first converting
events into dense representations that are then processed using standard CNNs. However …

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 …

Event cameras are novel sensors that report brightness changes in the form of a stream of
asynchronous “events” instead of intensity frames. They offer significant advantages with …

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

Spiking neural networks (SNNs) that enables energy efficient implementation on emerging
neuromorphic hardware are gaining more attention. Yet now, SNNs have not shown …

As a bio-inspired and emerging sensor, an event-based neuromorphic vision sensor has a
different working principle compared to the standard frame-based cameras, which leads to …

Spiking neural networks (SNNs) can potentially offer an efficient way of doing inference
because the neurons in the networks are sparsely activated and computations are event …

Event cameras are bio-inspired vision sensors that naturally capture the dynamics of a
scene, filtering out redundant information. This paper presents a deep neural network …