Papers Edge-computing
“Edge-computing” 태그가 달린 논문 1,279편 · 필터 해제
Microscopy is All You Need
We pose that microscopy offers an ideal real-world experimental environment for the development and deployment of active Bayesian and reinforcement learning methods. Indeed, the tremendous progress achieved by machine le…
AllEdge-computingEnergy-Efficient Deployment of Machine Learning Workloads on Neuromorphic Hardware
As the technology industry is moving towards implementing tasks such as natural language processing, path planning, image classification, and more on smaller edge computing devices, the demand for more efficient implemen…
Edge-computingimage-classificationImage ClassificationTime Series+1Streaming Video Analytics On The Edge With Asynchronous Cloud Support
Emerging Internet of Things (IoT) and mobile computing applications are expected to support latency-sensitive deep neural network (DNN) workloads. To realize this vision, the Internet is evolving towards an edge-computin…
Edge-computingGPUobject-detectionObject DetectionOpportunities for Intelligent Reflecting Surfaces in 6G-Empowered V2X Communications
This paper first describes the introduction of 6G-empowered V2X communications and IRS technology. Then it discusses different use case scenarios of IRS enabled V2X communications and reports recent advances in the exist…
Edge-computingMobile Edge Computing, Metaverse, 6G Wireless Communications, Artificial Intelligence, and Blockchain: Survey and Their Convergence
With the advances of the Internet of Things (IoT) and 5G/6G wireless communications, the paradigms of mobile computing have developed dramatically in recent years, from centralized mobile cloud computing to distributed f…
Cloud ComputingEdge-computingFIRE: A Failure-Adaptive Reinforcement Learning Framework for Edge Computing Migrations
In edge computing, users' service profiles are migrated due to user mobility. Reinforcement learning (RL) frameworks have been proposed to do so, often trained on simulated data. However, existing RL frameworks overlook …
Autonomous DrivingEdge-computingQ-Learningreinforcement-learning+1Google Coral-based edge computing person reidentification using human parsing combined with analytical method
Person reidentification (re-ID) is becoming one of the most significant application areas of computer vision due to its importance for science and social security. Due to enormous size and scale of camera systems it is b…
CPUEdge-computingGPUHuman ParsingIRS Assisted NOMA Aided Mobile Edge Computing with Queue Stability: Heterogeneous Multi-Agent Reinforcement Learning
By employing powerful edge servers for data processing, mobile edge computing (MEC) has been recognized as a promising technology to support emerging computation-intensive applications. Besides, non-orthogonal multiple a…
Edge-computingMulti-agent Reinforcement LearningReinforcement Learning (RL)An Edge Architecture Oriented Model Predictive Control Scheme for an Autonomous UAV Mission
In this article the implementation of a controller and specifically of a Model Predictive Controller (MPC) on an Edge Computing device, for controlling the trajectory of an Unmanned Aerial Vehicle (UAV) model, is examine…
Cloud ComputingEdge-computingFuture predictionModel Predictive ControlDeep Reinforcement Learning for Task Offloading in UAV-Aided Smart Farm Networks
The fifth and sixth generations of wireless communication networks are enabling tools such as internet of things devices, unmanned aerial vehicles (UAVs), and artificial intelligence, to improve the agricultural landscap…
Decision MakingDeep Reinforcement LearningEdge-computingimage-classification+4NanoFlowNet: Real-time Dense Optical Flow on a Nano Quadcopter
Nano quadcopters are small, agile, and cheap platforms that are well suited for deployment in narrow, cluttered environments. Due to their limited payload, these vehicles are highly constrained in processing power, rende…
Autonomous NavigationEdge-computingOptical Flow EstimationSemantic SegmentationVectorized Adjoint Sensitivity Method for Graph Convolutional Neural Ordinary Differential Equations
This document, as the title stated, is meant to provide a vectorized implementation of adjoint dynamics calculation for Graph Convolutional Neural Ordinary Differential Equations (GCDE). The adjoint sensitivity method is…
Edge-computingSensitivityMachine Learning Sensors for Diagnosis of COVID-19 Disease Using Routine Blood Values for Internet of Things Application
Healthcare digitalization requires effective applications of human sensors, when various parameters of the human body are instantly monitored in everyday life due to the Internet of Things (IoT). In particular, machine l…
DiagnosticEdge-computingTo Compute or not to Compute? Adaptive Smart Sensing in Resource-Constrained Edge Computing
We consider a network of smart sensors for an edge computing application that sample a time-varying signal and send updates to a base station for remote global monitoring. Sensors are equipped with sensing and compute, a…
Data CompressionEdge-computingActive Reconfigurable Intelligent Surface for Mobile Edge Computing
This paper investigates an active reconfigurable intelligent surface (RIS)-aided mobile edge computing (MEC) system. Compared with passive RIS, the active RIS is equipped with active reflective amplifier, which can effec…
Edge-computingControl-Oriented Power Allocation for Integrated Satellite-UAV Networks
This letter presents a sensing-communication-computing-control (SC3) integrated satellite unmanned aerial vehicle (UAV) network, where the UAV is equipped with on-board sensors, mobile edge computing (MEC) servers, base …
Edge-computingA Comprehensive Survey on Aerial Mobile Edge Computing: Challenges, State-of-the-Art, and Future Directions
Driven by the visions of Internet of Things (IoT), there is an ever-increasing demand for computation resources of IoT users to support diverse applications. Mobile edge computing (MEC) has been deemed a promising soluti…
Edge-computingSchedulingJoint Optimization of Resource Allocation, Phase Shift and UAV Trajectory for Energy-Efficient RIS-Assisted UAV-Enabled MEC Systems
The unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC) has been deemed a promising paradigm to provide ubiquitous communication and computing services for the Internet of Things (IoT). Besides, by intellig…
CPUEdge-computingDesign Automation for Fast, Lightweight, and Effective Deep Learning Models: A Survey
Deep learning technologies have demonstrated remarkable effectiveness in a wide range of tasks, and deep learning holds the potential to advance a multitude of applications, including in edge computing, where deep models…
Deep LearningEdge-computingModel CompressionNeural Architecture Search+1GreenKGC: A Lightweight Knowledge Graph Completion Method
Knowledge graph completion (KGC) aims to discover missing relationships between entities in knowledge graphs (KGs). Most prior KGC work focuses on learning embeddings for entities and relations through a simple scoring f…
Edge-computingKnowledge Graph CompletionKnowledge GraphsLink Prediction+2