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A Greedy Layer-Wise Learning Algorithm for Open-Circuit Fault Diagnosis of Grid-Connected Inverters
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
This paper introduces a greedy layer-wise learning algorithm to diagnose open-circuit faults of grid-connected inverters. Inverters play important roles in energy conversion, especially when converting direct current to ...
DistPrivacy: Privacy-Aware Distributed Deep Neural Networks in IoT surveillance systems
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
With the emergence of smart cities, Internet of Things (IoT) devices as well as deep learning technologies have witnessed an increasing adoption. To support the requirements of such paradigm in terms of memory and computation, ...
Deep Reinforcement Learning Algorithm for Smart Data Compression under NOMA-Uplink Protocol
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
One of the highly promising radio access strategies for enhancing performance in the next generation cellular communications is non-orthogonal multiple access (NOMA). NOMA offers a number of advantages including better ...
Deep Learning for RF-Based Drone Detection and Identification: A Multi-Channel 1-D Convolutional Neural Networks Approach
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
Commercial unmanned aerial vehicles, or drones, are getting increasingly popular in the last few years. The fact that these drones are highly accessible to public may bring a range of security and technical issues to ...
Energy-efficient networks selection based deep reinforcement learning for heterogeneous health systems
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Smart health systems improve the existing health services by integrating information and technology into health and medical practices. However, smart healthcare systems are facing major challenges including limited network ...
EEG-based Analysis Study for Patients Receiving Intravenous Antibiotic Medication
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
In this paper, we conduct a biological data collection and analysis study for patients undergoing routine planned intravenous antibiotic treatment. The acquired data (i.e., Electroencephalogram (EEG), temperature and blood ...
Smart and Secure Blockchain-based Healthcare System Using Deep Q-Learning
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Healthcare is one of the top priorities in modern society to provide better health facilities. Therefore, investments in health care systems increased rapidly, aligned with the population growth rate. Besides, the data ...
A Deep Learning Model for LoRa Signals Classification Using Cyclostationay Features
(
IEEE Computer Society
, 2021 , Conference Paper)
With the witnessed exponential growth of Internet of Things (IoT) nodes deployment following the emerging applications, multiple variants of technologies have been proposed to handle the IoT requirements. Among the proposed ...
Speech Command Recognition in Computationally Constrained Environments with a Quadratic Self-Organized Operational Layer
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Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Automatic classification of speech commands has revolutionized human computer interactions in robotic applications. However, employed recognition models usually follow the methodology of deep learning with complicated ...
A Scene-to-Speech Mobile based Application: Multiple Trained Models Approach
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Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
The concept of Scene-to-Speech (STS) is to recognize elements in a captured image or a video clip to speak loudly an informative textual content that describes the scene. The contemporary progression in convolution neural ...