Human activity recognition (HAR) is an emerging area of study and research field that
explores the development of automated systems to identify and categorize human activities …

Abstract Video-based Unsupervised Domain Adaptation (VUDA) method improves the
generalization of the video model enabling it to be applied to action recognition tasks in …

Abstract Multimodal Federated Learning (MMFL) is a novel machine learning technique that
enhances the capabilities of traditional Federated Learning (FL) to support collaborative …

In the context of the Internet of Things, utilizing the inherent inertial sensors in smartphones
for human activity recognition (HAR) has garnered considerable attention owing to its wide …

Multimodal federated learning (MFL) has emerged as a decentralized machine learning
paradigm, allowing multiple clients with different modalities to collaborate on training a …

Wearable sensors enable to monitor patients in their everyday living and working
environments. However, since they generate highly personal data, their protection from …

Federated learning is increasingly being considered for sensor-driven human activity
recognition, offering advantages in terms of privacy and scalability compared to centralized …

Background and objective: In recent times, medical imaging analysis (MIA) has seen an
increasing interest due to its core application in computer-aided diagnosis systems (CADs) …

In the evolving landscape of federated learning (FL), the integration of multimodal data
presents both unprecedented opportunities and significant challenges. Existing works fall …

The unprecedented technological advancements in Artificial Intelligence (AI) and the
Internet of Things (IoT) have given rise to ecosystems of intelligent, interconnected devices …