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[HTML][HTML] Federated learning for secure IoMT-applications in smart healthcare systems: A comprehensive review
Recent developments in the Internet of Things (IoT) and various communication
technologies have reshaped numerous application areas. Nowadays, IoT is assimilated into …
technologies have reshaped numerous application areas. Nowadays, IoT is assimilated into …
A state-of-the-art survey on solving non-iid data in federated learning
Federated Learning (FL) proposed in recent years has received significant attention from
researchers in that it can enable multiple clients to cooperatively train global models without …
researchers in that it can enable multiple clients to cooperatively train global models without …
Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: Challenges, recent advances, and future directions
Full leverage of the huge volume of data generated on a large number of user devices for
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …
Federated learning for internet of things: A comprehensive survey
The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …
Federated learning in edge computing: a systematic survey
Edge Computing (EC) is a new architecture that extends Cloud Computing (CC) services
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …
closer to data sources. EC combined with Deep Learning (DL) is a promising technology …
[HTML][HTML] Federated learning for IoT devices: Enhancing TinyML with on-board training
The spread of the Internet of Things (IoT) involving an uncountable number of applications,
combined with the rise of Machine Learning (ML), has enabled the rapid growth of pervasive …
combined with the rise of Machine Learning (ML), has enabled the rapid growth of pervasive …
Federated learning for computationally constrained heterogeneous devices: A survey
With an increasing number of smart devices like internet of things devices deployed in the
field, offloading training of neural networks (NNs) to a central server becomes more and …
field, offloading training of neural networks (NNs) to a central server becomes more and …
Federated learning-empowered mobile network management for 5G and beyond networks: From access to core
The fifth generation (5G) and beyond wireless networks are envisioned to provide an
integrated communication and computing platform that will enable multipurpose and …
integrated communication and computing platform that will enable multipurpose and …
Dynamic-fusion-based federated learning for COVID-19 detection
Medical diagnostic image analysis (eg, CT scan or X-Ray) using machine learning is an
efficient and accurate way to detect COVID-19 infections. However, the sharing of diagnostic …
efficient and accurate way to detect COVID-19 infections. However, the sharing of diagnostic …
Deep reinforcement learning assisted federated learning algorithm for data management of IIoT
The continuous expanded scale of the industrial Internet of Things (IIoT) leads to IIoT
equipments generating massive amounts of user data every moment. According to the …
equipments generating massive amounts of user data every moment. According to the …