Neuromorphic computing technologies will be important for the future of computing, but
much of the work in neuromorphic computing has focused on hardware development. Here …

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) aim to realize brain-inspired intelligence on neuromorphic
chips with high energy efficiency by introducing neural dynamics and spike properties. As …

The brain is the perfect place to look for inspiration to develop more efficient neural
networks. The inner workings of our synapses and neurons provide a glimpse at what the …

In the Internet-of-Things (IoT) era, billions of sensors and devices collect and process data
from the environment, transmit them to cloud centers, and receive feedback via the Internet …

Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …

Abstract Spiking Neural Networks (SNNs) have attracted enormous research interest due to
temporal information processing capability, low power consumption, and high biological …

Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …

Abstract Deep Spiking Neural Networks (SNNs) present optimization difficulties for gradient-
based approaches due to discrete binary activation and complex spatial-temporal dynamics …

Abstract Spiking Neural Networks (SNNs) provide an energy-efficient deep learning option
due to their unique spike-based event-driven (ie, spike-driven) paradigm. In this paper, we …