Decentralized federated learning: Fundamentals, state of the art, frameworks, trends, and challenges
In recent years, Federated Learning (FL) has gained relevance in training collaborative
models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the …
models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the …
[HTML][HTML] Federated learning for edge computing: A survey
New technologies bring opportunities to deploy AI and machine learning to the edge of the
network, allowing edge devices to train simple models that can then be deployed in practice …
network, allowing edge devices to train simple models that can then be deployed in practice …
Decentralized federated learning: A survey and perspective
Federated learning (FL) has been gaining attention for its ability to share knowledge while
maintaining user data, protecting privacy, increasing learning efficiency, and reducing …
maintaining user data, protecting privacy, increasing learning efficiency, and reducing …
A systematic review on federated learning in medical image analysis
MF Sohan, A Basalamah - IEEE Access, 2023 - ieeexplore.ieee.org
Federated Learning (FL) obtained a lot of attention to the academic and industrial
stakeholders from the beginning of its invention. The eye-catching feature of FL is handling …
stakeholders from the beginning of its invention. The eye-catching feature of FL is handling …
A systematic review of federated learning incentive mechanisms and associated security challenges
In response to various privacy risks, researchers and practitioners have been exploring
different paradigms that can leverage the increased computational capabilities of consumer …
different paradigms that can leverage the increased computational capabilities of consumer …
A comprehensive review on federated learning based models for healthcare applications
A disease is an abnormal condition that negatively impacts the functioning of the human
body. Pathology determines the causes behind the disease and identifies its development …
body. Pathology determines the causes behind the disease and identifies its development …
[HTML][HTML] Hierarchical trajectory planning for narrow-space automated parking with deep reinforcement learning: A federated learning scheme
Collision-free trajectory planning in narrow spaces has become one of the most challenging
tasks in automated parking scenarios. Previous optimization-based approaches can …
tasks in automated parking scenarios. Previous optimization-based approaches can …
Smart Policy Control for Securing Federated Learning Management System
AP Kalapaaking, I Khalil… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …
healthcare systems, and various real-world applications have resulted in the generation of …
Independence and unity: Unseen domain segmentation based on federated learning
G Yuan, J Li, Y Huang, Z Xie, J Pang… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
The distinct attributes of Internet of Things (IoTs) devices, including the disparity between
training and testing data distributions and limited availability of training data, pose …
training and testing data distributions and limited availability of training data, pose …
Towards quantum federated learning
Quantum Federated Learning (QFL) is an emerging interdisciplinary field that merges the
principles of Quantum Computing (QC) and Federated Learning (FL), with the goal of …
principles of Quantum Computing (QC) and Federated Learning (FL), with the goal of …