Introduction The field of machine learning has undergone a significant transformation with
the progress of deep artificial neural networks (ANNs) and the growing accessibility of …

The brain has computational capabilities that surpass those of modern systems, being able
to solve complex problems efficiently in a simple way. Neuromorphic engineering aims to …

The rapid expansion of information systems in all areas of society demands more powerful,
efficient, and low‐energy consumption computing systems. Neuromorphic engineering has …

Spiking neural networks (SNNs) have gained attention as models of sparse and event-
driven communication of biological neurons, and as such have shown increasing promise …

The field of machine learning has been greatly transformed with the advancement of deep
artificial neural networks (ANNs) and the increased availability of annotated data. Spiking …

The need for processing at the edge the increasing amount of data that is being produced by
multitudes of sensors has led to the demand for mode power efficient computational …

The brain is considered one of the most powerful and efficient machines in existence. This is
why neuromorphic engineering is trying to mimic biology to develop new systems that …

Small satellite constellations have shown tremendous success for Earth observation
missions and can mimic the performance of large satellite platforms while being cheaper …

The brain is considered one of the most powerful and efficient machines in existence. This is
why neuromorphic engineering is trying to mimic biology to develop new systems that …

Real-time image processing and pattern recognition applications have found a new
paradigm in neuromorphic computing systems. In this paper, we quantitatively compare …