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السجلات المعروضة 41 -- 50 من 53
Energy-Efficient Device Assignment and Task Allocation in Multi-Orchestrator Mobile Edge Learning
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Mobile Edge Learning (MEL) is a decentralized learning paradigm that enables resource-constrained IoT devices to either learn a shared model without sharing the data, or to distribute the learning task with the data to ...
Patient-Driven Network Selection in multi-RAT Health Systems Using Deep Reinforcement Learning
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
The recent pandemic along with the rapid increase in the number of patients that require continuous remote monitoring imposes several challenges to support the high quality of services (QoS) in remote health applications. ...
Crowd counting Using DRL-based segmentation and RL-based density estimation
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
People counting is one of the computer vision tasks that can be useful for crowd management. In addition, estimating the crowdedness of a surveilled scene for crowd behavior analysis is one of the prominent challenges in ...
RLENS: RL-based Energy-Efficient Network Selection Framework for IoMT
(
IEEE
, 2022 , Conference Paper)
With the emergence of smart health (s-health) applications and services, several requirements for quality have arisen to foresee and react instantaneously to emergency circumstances. Such requirements demand fast-acting ...
MMRL: A Multi-Modal Reinforcement Learning Technique for Energy-efficient Medical IoT Systems
(
IEEE
, 2021 , Conference Paper)
The Internet of Medical Things (IoMT) couples the rapid growth of Internet of things (IoT) technologies with smart health systems, leveraging wireless battery-operated devices for remote health monitoring. Since 2019, a ...
Incentive-based Resource Allocation for Mobile Edge Learning
(
IEEE
, 2022 , Conference Paper)
Mobile Edge Learning (MEL) is a learning paradigm that facilitates training of Machine Learning (ML) models over resource-constrained edge devices. MEL consists of an orchestrator, which represents the model owner of the ...
AirEye: UAV-Based Intelligent DRL Mobile Target Visitation
(2022 , Conference Paper)
From traffic monitoring to livestock tracking, and military reconnaissance to marine discovery, unmanned aerial vehicles (UAVs) are indispensable. Its dependence on a battery for power supply limits the flight time to visit ...
RL-Assisted Energy-Aware User-Edge Association for IoT-based Hierarchical Federated Learning
(2022 , Conference Paper)
The extremely heavy global reliance on IoT devices is causing enormous amounts of data to be gathered and shared in IoT networks. Such data need to efficiently be used in training and deploying of powerful artificially ...
On the Modeling of Reliability in Extreme Edge Computing Systems
(
IEEE
, 2022 , Conference Paper)
Extreme edge computing (EEC) refers to the end-most part of edge computing wherein computational tasks and edge services are deployed only on extreme edge devices (EEDs). EEDs are consumer or user-owned devices that offer ...
Region of Interest Optimization for Delay-sensitive Telemedicine Applications
(
IEEE
, 2022 , Conference Paper)
Telemedicine is a rising technology that is gaining a lot of interest in the recent decades. Several applications of telemedicine are delay-sensitive and need to be operated in real-time. One of which is surgical tele-mentoring ...