Machine Learning (ML) has emerged as an attractive and viable technique to provide
effective solutions for a wide range of application domains. An important application domain …

The Metaverse, positioned as the next frontier of the Internet, has the ambition to forge a
virtual shared realm characterized by immersion, hyper-spatiotemporal dynamics, and self …

Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning
(DL) is already present in many applications ranging from computer vision for medicine to …

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 …

With the ambitious plans of renewal and expansion of industrialization in many countries,
the efficiency, agility and cost savings potentially resulting from the application of industrial …

Machine Learning (ML) algorithms, specifically supervised learning, are widely used in
modern real-world applications, which utilize Computational Intelligence (CI) as their core …

Numerous studies have demonstrated, in-depth, the vulnerability of the deep reinforcement
learning (DRL) model's elements (eg, reward), which is a factor limiting the widespread …

Adversarial examples have emerged as a significant threat to machine learning algorithms,
especially to the convolutional neural networks (CNNs). In this paper, we propose two …

Machine learning (ML) models are now a key component for many applications. However,
machine learning based systems (MLBSs), those systems that incorporate them, have …

The increased automation and connectivity of vehicles and road infrastructure can make
future transportation systems more efficient and smarter and enable new transportation …