Federated learning (FL) becomes popular and has shown great potentials in training large-
scale machine learning (ML) models without exposing the owners' raw data. In FL, the data …

Intelligent transportation systems (ITSs) have been fueled by the rapid development of
communication technologies, sensor technologies, and the Internet of Things (IoT) …

Federated learning (FL), as a distributed machine learning technology, allows large-scale
nodes to utilize local datasets for model training and sharing without revealing privacy …

New technological advancements in wireless networks have enlarged the number of
connected devices. The unprecedented surge of data volume in wireless systems …

Research on smart connected vehicles has recently targeted the integration of vehicle-to-
everything (V2X) networks with Machine Learning (ML) tools and distributed decision …

The concept of federated learning (FL) is becoming increasingly popular as a method for
training collaborative models without loss the sensitive information. The term has become …

Due to the protection of ship** data privacy, ship** companies rarely share ship**
raw data. Therefore, how to protect ship** data privacy is a crucial issue when predicting …

Over the last few years, Electric Vehicles (EVs) have been gaining interest as a result of their
ability to reduce vehicle emissions. Develo** an intelligent system to manage EVs …

While the convergence of Artificial Intelligence (AI) techniques with improved information
technology systems ensured enormous benefits to the Internet of Vehicles (IoVs) systems, it …

Recently, federated learning (FL) as a new learning paradigm allows multi-party to
collaboratively train a shared global model with privacy protection. However, vanilla FL …