In recent years, deep learning has revolutionized the field of machine learning, for computer
vision in particular. In this approach, a deep (multilayer) artificial neural network (ANN) is …

Artificial neural networks have been used as a powerful processing tool in various areas
such as pattern recognition, control, robotics, and bioinformatics. Their wide applicability has …

Dense crossbar arrays of non-volatile memory (NVM) devices represent one possible path
for implementing massively-parallel and highly energy-efficient neuromorphic computing …

Applications that generate huge amounts of data in the form of fast streams are becoming
increasingly prevalent, being therefore necessary to learn in an online manner. These …

The combination of neuromorphic visual sensors and spiking neural network offers a high
efficient bio-inspired solution to real-world applications. However, processing event-based …

Biological intelligence processes information using impulses or spikes, which makes those
living creatures able to perceive and act in the real world exceptionally well and outperform …

Currently, machine learning (ML) techniques are at the heart of smart cyber-physical
systems (CPSs) and Internet-of-Things (loT). This article discusses various challenges and …

In the recent years, the spiking neural network (SNN) has attracted increasing attention due
to its low energy consumption and online learning potential. However, the design of SNN …

The emergence of biorobotic autonomous undersea vehicle (AUV) as a focus for discipline-
integrated research in the context of underwater propulsion and maneuvering is considered …

This review article gives a high-level overview of the approaches across different scales of
organization and levels of abstraction. The studies covered in this paper include …