Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …

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 …

Artificial neural networks (ANNs), a popular path towards artificial intelligence, have
experienced remarkable success via mature models, various benchmarks, open-source …

The field of neuromorphic computing promises extremely low-power and low-latency
sensing and processing. Challenges in transferring learning algorithms from traditional …

Neuromorphic vision sensor is a new bio-inspired imaging paradigm that reports
asynchronous, continuously per-pixel brightness changes called'events' with high temporal …

Event-based cameras display great potential for a variety of tasks such as high-speed
motion detection and navigation in low-light environments where conventional frame-based …

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

The combination of spiking neural networks and event-based vision sensors holds the
potential of highly efficient and high-bandwidth optical flow estimation. This paper presents …

The explosion of “big data” applications imposes severe challenges of speed and scalability
on traditional computer systems. As the performance of traditional Von Neumann machines …

Spiking neural networks (SNNs) are a promising energy-efficient alternative to artificial
neural networks (ANNs) due to their rich dynamics, capability to process spatiotemporal …