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Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data
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Elsevier B.V.
, 2022 , Article)
Federated Learning (FL) is a distributed learning methodology that allows multiple nodes to cooperatively train a deep learning model, without the need to share their local data. It is a promising solution for telemonitoring ...
A Weighted Machine Learning-Based Attacks Classification to Alleviating Class Imbalance
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
The Industrial Internet of Things (IIoT) has become very popular in recent years. However, IIoT is still an attractive and vulnerable target for attackers to exploit and experiment with different types of attacks. To ...
FSC-Set: Counting, Localization of Football Supporters Crowd in the Stadiums
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Counting the number of people in a crowd has gained attention in the last decade. Due to its benefit to many applications such as crowd behavior analysis, crowd management, and video surveillance systems, etc. Counting ...
Evolution of Internet of Things from Blockchain to IOTA: A Survey
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Internet of Things (IoT) is the new paradigm to the scaling nature of things and their elements, interconnected, exchanging data over a network supported with nodes. The Ubiquitous use of tiny devices and embedded sensor ...
MEdge-Chain: Leveraging Edge Computing and Blockchain for Efficient Medical Data Exchange
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Medical data exchange between diverse e-health entities can lead to a better healthcare quality, improving the response time in emergency conditions, and a more accurate control of critical medical events (e.g., national ...
Distributed CNN Inference on Resource-Constrained UAVs for Surveillance Systems: Design and Optimization
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Unmanned aerial vehicles (UAVs) have attracted great interest in the last few years owing to their ability to cover large areas and access difficult and hazardous target zones, which is not the case of traditional systems ...
Deep Reinforcement Learning for Network Selection over Heterogeneous Health Systems
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IEEE Computer Society
, 2022 , Article)
Smart health systems improve our quality oflife by integrating diverse information and technologies into health and medical practices. Such technologies can significantly improve the existing health services. However, ...
Spatiotemporal data mining: a survey on challenges and open problems
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Springer Science and Business Media B.V.
, 2022 , Article)
Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic interplay between space and time. Several available surveys capture STDM advances and report a wealth of important progress in this field. However, ...
Optimal User-Edge Assignment in Hierarchical Federated Learning Based on Statistical Properties and Network Topology Constraints
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IEEE Computer Society
, 2022 , Article)
Distributed learning algorithms aim to leverage distributed and diverse data stored at users' devices to learn a global phenomena by performing training amongst participating devices and periodically aggregating their local ...
Energy-Aware Distributed Edge ML for mHealth Applications with Strict Latency Requirements
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Edge machine learning (Edge ML) is expected to serve as a key enabler for real-time mobile health (mHealth) applications. However, its reliability is governed by the limited energy and computing resources of user equipment ...