Federated Learning (FL) has emerged as a significant advancement in the field of Artificial
Intelligence (AI), enabling collaborative model training across distributed devices while …

The intelligent optimization framework for predicting the vulnerable range of tumor cells
using Internet of Things (IoT) provides a robust and efficient solution for monitoring …

Federated learning (FL) is a machine learning technique that allows for on-site data
collection and processing without sacrificing data privacy and transmission. Heterogeneity is …

Federated learning (FL) provides convenience for cross-domain machine learning
applications and has been widely studied. However, the original FL is still vulnerable to …

With the emergence of intelligent services and applications powered by artificial intelligence
(AI), the Internet of Things (IoT) affects many aspects of our daily lives. Traditional …

The widespread adoption of Internet of Things (IoT) devices in smart cities, intelligent
healthcare systems, and various real-world applications have resulted in the generation of …

Barriers are utilized for various tasks in security, environmental monitoring, penetration
detection and reconnaissance. It is highly necessary to consider how to support pedestrian …

In the realm of machine learning (ML) systems featuring client-host connections, the
enhancement of privacy security can be effectively achieved through federated learning (FL) …

Underwater acoustic sensor networks (UASNs) have been widely deployed in many areas,
such as marine ranching, naval applications, and marine disaster warning systems. The …

In the field of Person Re-identification (ReID), addressing the demands of practical
applications in diverse and uncontrollable unseen domains necessitates a focus on Domain …