Papers Edge-computing
“Edge-computing” 태그가 달린 논문 1,279편 · 필터 해제
Need of 6G for the Metaverse Realization
The concept of the Metaverse aims to bring a fully-fledged extended reality environment to provide next generation applications and services. Development of the Metaverse is backed by many technologies, including, 5G, ar…
Edge-computingPRISM: Privacy Preserving Healthcare Internet of Things Security Management
Consumer healthcare Internet of Things (IoT) devices are gaining popularity in our homes and hospitals. These devices provide continuous monitoring at a low cost and can be used to augment high-precision medical equipmen…
Anomaly DetectionEdge-computingManagementPrivacy PreservingMind Your Heart: Stealthy Backdoor Attack on Dynamic Deep Neural Network in Edge Computing
Transforming off-the-shelf deep neural network (DNN) models into dynamic multi-exit architectures can achieve inference and transmission efficiency by fragmenting and distributing a large DNN model in edge computing scen…
Backdoor AttackEdge-computingHigh-Throughput, High-Performance Deep Learning-Driven Light Guide Plate Surface Visual Quality Inspection Tailored for Real-World Manufacturing Environments
Light guide plates are essential optical components widely used in a diverse range of applications ranging from medical lighting fixtures to back-lit TV displays. In this work, we introduce a fully-integrated, high-throu…
Defect DetectionEdge-computingVocal Bursts Intensity PredictionUnified, User and Task (UUT) Centered Artificial Intelligence for Metaverse Edge Computing
The Metaverse can be considered the extension of the present-day web, which integrates the physical and virtual worlds, delivering hyper-realistic user experiences. The inception of the Metaverse brings forth many ecosys…
Edge-computingEdge Computing for Semantic Communication Enabled Metaverse: An Incentive Mechanism Design
Semantic communication (SemCom) and edge computing are two disruptive solutions to address emerging requirements of huge data communication, bandwidth efficiency and low latency data processing in Metaverse. However, edg…
Edge-computingSemantic CommunicationMist and Edge Computing Cyber-Physical Human-Centered Systems for Industry 5.0: A Cost-Effective IoT Thermal Imaging Safety System
While many companies worldwide are still striving to adjust to Industry 4.0 principles, the transition to Industry 5.0 is already underway. Under such a paradigm, Cyber-Physical Human-centered Systems (CPHSs) have emerge…
Edge-computingEEG Opto-processor: epileptic seizure detection using diffractive photonic computing units
Electroencephalography (EEG) analysis extracts critical information from brain signals, which has provided fundamental support for various applications, including brain-disease diagnosis and brain-computer interface. How…
Brain Computer Interfacechannel selectionEdge-computingEEG+2Vicious Classifiers: Assessing Inference-time Data Reconstruction Risk in Edge Computing
Privacy-preserving inference in edge computing paradigms encourages the users of machine-learning services to locally run a model on their private input and only share the models outputs for a target task with the server…
Edge-computingPrivacy PreservingReconstruction AttackToward Multi-Service Edge-Intelligence Paradigm: Temporal-Adaptive Prediction for Time-Critical Control over Wireless
Time-critical control applications typically pose stringent connectivity requirements for communication networks. The imperfections associated with the wireless medium such as packet losses, synchronization errors, and v…
Edge-computingHADAS: Hardware-Aware Dynamic Neural Architecture Search for Edge Performance Scaling
Dynamic neural networks (DyNNs) have become viable techniques to enable intelligence on resource-constrained edge devices while maintaining computational efficiency. In many cases, the implementation of DyNNs can be sub-…
Computational EfficiencyDynamic neural networksEdge-computingNeural Architecture SearchTHOR -- A Neuromorphic Processor with 7.29G TSOP$^2$/mm$^2$Js Energy-Throughput Efficiency
Neuromorphic computing using biologically inspired Spiking Neural Networks (SNNs) is a promising solution to meet Energy-Throughput (ET) efficiency needed for edge computing devices. Neuromorphic hardware architectures t…
Edge-computingDeepFT: Fault-Tolerant Edge Computing using a Self-Supervised Deep Surrogate Model
The emergence of latency-critical AI applications has been supported by the evolution of the edge computing paradigm. However, edge solutions are typically resource-constrained, posing reliability challenges due to heigh…
Edge-computingFault DetectionSchedulingSelf-Supervised LearningGenerative Data Augmentation for Non-IID Problem in Decentralized Clinical Machine Learning
Swarm learning (SL) is an emerging promising decentralized machine learning paradigm and has achieved high performance in clinical applications. SL solves the problem of a central structure in federated learning by combi…
Data AugmentationEdge-computingFederated LearningEdge Video Analytics: A Survey on Applications, Systems and Enabling Techniques
Video, as a key driver in the global explosion of digital information, can create tremendous benefits for human society. Governments and enterprises are deploying innumerable cameras for a variety of applications, e.g., …
Edge-computingDesign and Prototyping Distributed CNN Inference Acceleration in Edge Computing
For time-critical IoT applications using deep learning, inference acceleration through distributed computing is a promising approach to meet a stringent deadline. In this paper, we implement a working prototype of a new …
Distributed ComputingEdge-computingModel CompressionModel Selection+1Attention-based Feature Compression for CNN Inference Offloading in Edge Computing
This paper studies the computational offloading of CNN inference in device-edge co-inference systems. Inspired by the emerging paradigm semantic communication, we propose a novel autoencoder-based CNN architecture (AECNN…
DecoderEdge-computingFeature CompressionSemantic CommunicationProbabilistic Time Series Forecasting for Adaptive Monitoring in Edge Computing Environments
With increasingly more computation being shifted to the edge of the network, monitoring of critical infrastructures, such as intermediate processing nodes in autonomous driving, is further complicated due to the typicall…
Autonomous DrivingEdge-computingProbabilistic Time Series ForecastingTime Series+2Benchmarking Edge Computing Devices for Grape Bunches and Trunks Detection using Accelerated Object Detection Single Shot MultiBox Deep Learning Models
Purpose: Visual perception enables robots to perceive the environment. Visual data is processed using computer vision algorithms that are usually time-expensive and require powerful devices to process the visual data in …
BenchmarkingEdge-computingGPUobject-detection+1Bi-directional Digital Twin and Edge Computing in the Metaverse
The Metaverse has emerged to extend our lifestyle beyond physical limitations. As essential components in the Metaverse, digital twins (DTs) are the real-time digital replicas of physical items. Multi-access edge computi…
Continual LearningEdge-computing