Remote sensing (RS) imagery provides invaluable insights into characterizing the Earth's
land surface within the scope of Earth observation (EO). Technological advances in capture …

Integrating machine learning (ML) and blockchain technologies presents a groundbreaking
approach to real-time fraud detection and prevention, addressing the growing complexity …

Federated learning (FL) is a decentralized machine learning (ML) technique that enables
multiple clients to collaboratively train a common ML model without them having to share …

Cross-training has become a promising strategy to handle data heterogeneity problem in
federated learning, which re-train a local model across different clients to improve its …

Currently, the application of big data and artificial intelligence (AI) in financial credit risk
management is a research hot spot. Most research has focused on using data and AI …

This work presents AttFL, a federated learning framework designed to continuously improve
a personalized deep neural network for efficiently analyzing time-series data generated from …

Cybersecurity is an ever-important aspect of our interconnected world, but security defenses
lag behind the adversaries who with increasing sophistication seek to disrupt cybersystems …

The control, governance, and management of the web have become increasingly
centralised, resulting in security, privacy, and censorship concerns. Decentralised initiatives …

Multimedia retrieval models need the ability to extract useful information from large-scale
data for clients. As an important part of multimedia retrieval, image classification model …

The recent advancements in the Internet of Medical Things (IoMT) have significantly
contributed to improving personalized medicine and patient diagnosis and monitoring …