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Secrecy Outage Performance of Ground-to-Air Communications with Multiple Aerial Eavesdroppers and Its Deep Learning Evaluation
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
In this letter, we study the secure information transmission from a ground base station (GBS) to a legitimate unmanned aerial vehicle (UAV) user, in the presence of multiple UAV eavesdroppers. To enhance the secrecy ...
Uncertainty awareness in transmission line fault analysis: A deep learning based approach
(
Elsevier Ltd
, 2022 , Article)
With the expansion of the modern power system, it is of increasing significance to analyze the faults in the transmission lines. As the transmission line is the most exposed element of a power system, it is prone to different ...
A deep learning-based approach for fault diagnosis of current-carrying ring in catenary system
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Springer Science and Business Media Deutschland GmbH
, 2021 , Article)
In the Industrial Internet of Things, the deep learning-based methods are used to help solve various problems. The current-carrying ring as one of important components on the catenary system which is always small in the ...
Real-Time Patient-Specific ECG Classification by 1D Self-Operational Neural Networks
(
IEEE Computer Society
, 2021 , Article)
Despite the proliferation of numerous deep learning methods proposed for generic ECG classification and arrhythmia detection, compact systems with the real-time ability and high accuracy for classifying patient-specific ...
Disaster related social media content processing for sustainable cities
(
Elsevier
, 2021 , Article)
The current study offers a hybrid convolutional neural networks (CNN) model that filters relevant posts and categorises them into several humanitarian classifications using both character and word embedding of textual ...
Intelligent Task Offloading and Energy Allocation in the UAV-Aided Mobile Edge-Cloud Continuum
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
The arrival of big data and the Internet of Things (IoT) era greatly promotes innovative in-network computing techniques, where the edge-cloud continuum becomes a feasible paradigm in handling multi-dimensional resources ...
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 ...
Communication-efficient hierarchical federated learning for IoT heterogeneous systems with imbalanced data
(
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 Deep Reinforcement Learning Framework for Data Compression in Uplink NOMA-SWIPT Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
<comment< Non-orthogonal multiple access (NOMA) shall play an important role in the current and foreseeable design of 5G and beyond networks. NOMA allows multiple users to share the same time-frequency ...
Multi-layer security scheme for implantable medical devices
(
Springer
, 2020 , Article)
Internet of Medical Things (IoMTs) is fast emerging, thereby fostering rapid advances in the areas of sensing, actuation and connectivity to significantly improve the quality and accessibility of health care for everyone. ...