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 …

The development of brain-inspired neuromorphic computing architectures as a paradigm for
Artificial Intelligence (AI) at the edge is a candidate solution that can meet strict energy and …

Why do neurons communicate through spikes? By definition, spikes are all-or-none neural
events which occur at continuous times. In other words, spikes are on one side binary …

Event cameras are sensors of great interest for many applications that run in low-resource
and challenging environments. They log sparse illumination changes with high temporal …

Human activity recognition (HAR) is a key enabling technology for a wide range of emerging
applications. Although multimodal sensing systems are essential for capturing complex and …

Neuromorphic vision sensing (NVS) devices represent visual information as sequences of
asynchronous discrete events (aka,“spikes”) in response to changes in scene reflectance …

The spiking neural network (SNN) mimics the information-processing operation in the
human brain. Directly applying backpropagation to the training of the SNN still has a …

In this paper we present an event aggregation strategy to convert the output of an event
camera into frames processable by traditional Computer Vision algorithms. The proposed …

Autonomous Driving (AD) related features provide new forms of mobility that are also
beneficial for other kind of intelligent and autonomous systems like robots, smart …

Event-based neural networks are currently being explored as efficient solutions for
performing AI tasks at the extreme edge. To fully exploit their potential, event-based neural …