In recent years, Federated Learning (FL) has gained relevance in training collaborative
models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the …

Federated learning (FL) is a secure distributed machine learning paradigm that addresses
the issue of data silos in building a joint model. Its unique distributed training mode and the …

Federated learning is a privacy-preserving machine learning technique that trains models
across multiple devices holding local data samples without exchanging them. There are …

The research on the sixth-generation (6G) wireless communications for the development of
future mobile communication networks has been officially launched around the world. 6G …

Driven by the ever-increasing requirements of autonomous vehicles, such as traffic
monitoring and driving assistant, deep learning-based object detection (DL-OD) has been …

Healthcare fraud is a global problem affecting both develo** and developed countries. It is
the deliberate attempt of the perpetrators to take undue advantage of the inefficiencies in …

Unmanned aerial vehicles (UAVs) have recently established their capacity to provide cost-
effective and credible solutions for various real-world scenarios. UAVs provide an immense …

Intelligent Transportation Systems (ITS) operate within a highly intricate and dynamic
environment characterized by complex spatial and temporal dynamics at various scales …

In vehicular ad-hoc networks (VANET), federated learning enables vehicles to
collaboratively train a global model for intelligent transportation without sharing their local …

Artificial Intelligence (AI) is an emerging technology that finds its application in various
industries. Integration of AI in Unmanned Aerial Vehicles (UAVs) can lead to tremendous …