Multimodal federated learning on iot data Y Zhao, P Barnaghi, H Haddadi IoTDI, 202205 PUB Cross-modal federated human activity recognition via modality-agnostic and modality-specific representation learning X Yang, B Xiong, Y Huang, C Xu AAAI, 2022 PUB Towards optimal multi-modal federated learni...
Federated learning is proposed as an alternative to centralized machine learning since its client-server structure provides better privacy protection and scalability in real-world applications. In many applications, such as smart homes with Internet-of-Things (IoT) devices, local data on clients are ...
Multimodal Federated Learning on IoT Data Towards Optimal Multi-Modal Federated Learning on Non-IID Data with Hierarchical Gradient Blending
Smart cars, smartphones and other devices in the Internet of Things (IoT), which usually have more than one sensors, produce multimodal data. Federated Learning supports collecting a wealth of multimodal data from different devices without sharing raw data. Transfer Learning methods help transfer ...
Additionally, to overcome issues of data privacy and regulation associated with collecting training data in IoT systems, we utilize Federated Learning (FL) to train our model This collaborative machine-learning approach enables data parties to train models while preserving data privacy. Our proposed ...
The new approach relies on Federated Learning (FL) which is a Machine Learning paradigm that can support data management and privacy by training decentralized models collaboratively without effective data exchange. The new approach also combines Photoplethysmography and Electrocardiogram signals which improves...
Machine learning is frequently being leveraged to tackle problems in the health sector including utilization for clinical decision-support. Its use has historically been focused on single modal data. Attempts to improve prediction and mimic the multimoda
Based on the technology trends and best practices in the field, the Services Conference Federation (SCF) will continue serving as the conference umbrella's code name for all services-related conferences. SCF 2024 defines the future of New ABCDE (AI, Blockchain, Cloud, BigData & IOT) and Digi...
Machine learning is frequently being leveraged to tackle problems in the health sector including utilization for clinical decision-support. Its use has historically been focused on single modal data. Attempts to improve prediction and mimic the multimoda
2021). It encompasses the utilization of diverse digital instruments such as wearables, telehealth, electronic health records (EHR), AI, Internet of Things (IoTs), and big data analytics to transform healthcare provision. The utilization of healthcare devices based on IoT, denoting tools embedded...