Objectives: This article explores the integration of advanced ensemble machine learning
methods within precision agriculture, aiming to enhance the reliability and practical utility of …

This paper addresses the growing demand for healthcare systems, particularly among the
elderly population. The need for these systems arises from the desire to enable patients and …

Federated learning can achieve multi-party data-collaborative applications while
safeguarding personal privacy. However, the process often leads to a decline in the quality …

Edge-AI, the convergence of edge computing and artificial intelligence (AI), has become a
promising paradigm that enables the deployment of advanced AI models at the network …

Technologies for recognizing facial attributes like race, gender, age, and emotion have
several applications, such as surveillance, advertising content, sentiment analysis, and the …

Healthcare data is often split into medium/small-sized collections across multiple hospitals
and access to it is encumbered by privacy regulations. This brings difficulties to use them for …

Abstract Vertical Federated Learning (VFL) is gaining increasing attention due to its ability to
enable multiple parties to collaboratively train a privacy-preserving model using vertically …

As network connectivity increasingly shapes modern vehicular applications, in-advance
knowledge of Quality-of-Service (QoS) degradation could unlock the potential for efficient …