Papers Edge-computing
“Edge-computing” 태그가 달린 논문 1,279편 · 필터 해제
Towards General Industrial Intelligence: A Survey of Continual Large Models in Industrial IoT
Industrial AI is transitioning from traditional deep learning models to large-scale transformer-based architectures, with the Industrial Internet of Things (IIoT) playing a pivotal role. IIoT evolves from a simple data p…
Cloud ComputingContinual LearningEdge-computingSafeTail: Efficient Tail Latency Optimization in Edge Service Scheduling via Computational Redundancy Management
Optimizing tail latency while efficiently managing computational resources is crucial for delivering high-performance, latency-sensitive services in edge computing. Emerging applications, such as augmented reality, requi…
Edge-computingManagementSchedulingEmulating Brain-like Rapid Learning in Neuromorphic Edge Computing
Achieving personalized intelligence at the edge with real-time learning capabilities holds enormous promise in enhancing our daily experiences and helping decision making, planning, and sensing. However, efficient and re…
Edge-computingOne-Shot LearningTransfer LearningCGRA4ML: A Framework to Implement Modern Neural Networks for Scientific Edge Computing
Scientific edge computing increasingly relies on hardware-accelerated neural networks to implement complex, near-sensor processing at extremely high throughputs and low latencies. Existing frameworks like HLS4ML are effe…
Edge-computingJoint Offloading and Beamforming Design in Integrating Sensing, Communication, and Computing Systems: A Distributed Approach
When applying integrated sensing and communications (ISAC) in future mobile networks, many sensing tasks have low latency requirements, preferably being implemented at terminals. However, terminals often have limited com…
Edge-computingISACERX: A Fast Real-Time Anomaly Detection Algorithm for Hyperspectral Line Scanning
Detecting unexpected objects (anomalies) in real time has great potential for monitoring, managing, and protecting the environment. Hyperspectral line-scan cameras are a low-cost solution that enhance confidence in anoma…
Anomaly DetectionCPUEdge-computingDRL-Based Federated Self-Supervised Learning for Task Offloading and Resource Allocation in ISAC-Enabled Vehicle Edge Computing
Intelligent Transportation Systems (ITS) leverage Integrated Sensing and Communications (ISAC) to enhance data exchange between vehicles and infrastructure in the Internet of Vehicles (IoV). This integration inevitably i…
CPUEdge-computingISACSelf-Supervised LearningMONAS: Efficient Zero-Shot Neural Architecture Search for MCUs
Neural Architecture Search (NAS) has proven effective in discovering new Convolutional Neural Network (CNN) architectures, particularly for scenarios with well-defined accuracy optimization goals. However, previous appro…
Edge-computingNeural Architecture SearchA Lightweight Human Pose Estimation Approach for Edge Computing-Enabled Metaverse with Compressive Sensing
The ability to estimate 3D movements of users over edge computing-enabled networks, such as 5G/6G networks, is a key enabler for the new era of extended reality (XR) and Metaverse applications. Recent advancements in dee…
Compressive SensingEdge-computingPose EstimationA proof of contribution in blockchain using game theoretical deep learning model
Building elastic and scalable edge resources is an inevitable prerequisite for providing platform-based smart city services. Smart city services are delivered through edge computing to provide low-latency applications. H…
Edge-computingGraph Neural NetworkSchedulingEnergy-Efficient Spiking Recurrent Neural Network for Gesture Recognition on Embedded GPUs
Implementing AI algorithms on event-based embedded devices enables real-time processing of data, minimizes latency, and enhances power efficiency in edge computing. This research explores the deployment of a spiking recu…
Edge-computingGesture RecognitionGPUWhen In-memory Computing Meets Spiking Neural Networks -- A Perspective on Device-Circuit-System-and-Algorithm Co-design
This review explores the intersection of bio-plausible artificial intelligence in the form of Spiking Neural Networks (SNNs) with the analog In-Memory Computing (IMC) domain, highlighting their collective potential for l…
Edge-computingTReX- Reusing Vision Transformer's Attention for Efficient Xbar-based Computing
Due to the high computation overhead of Vision Transformers (ViTs), In-memory Computing architectures are being researched towards energy-efficient deployment in edge-computing scenarios. Prior works have proposed effici…
CoLAEdge-computingEnhancing Transferability of Adversarial Attacks with GE-AdvGAN+: A Comprehensive Framework for Gradient Editing
Transferable adversarial attacks pose significant threats to deep neural networks, particularly in black-box scenarios where internal model information is inaccessible. Studying adversarial attack methods helps advance t…
Adversarial AttackComputational EfficiencyEdge-computingCombining features on vertical ground reaction force signal analysis for multiclass diagnosing neurodegenerative diseases
Neurodegenerative diseases (NDDs), which are caused by the degeneration of neurons and their functions, affect a significant part of the world’s population. Although gait disorders are one of the critical and common ma…
DiagnosticDynamic Time WarpingEdge-computingMulti-class ClassificationEdge-Cloud Collaborative Motion Planning for Autonomous Driving with Large Language Models
Integrating large language models (LLMs) into autonomous driving enhances personalization and adaptability in open-world scenarios. However, traditional edge computing models still face significant challenges in processi…
Autonomous DrivingDrift DetectionEdge-computingMotion PlanningFeasibility of assessing cognitive impairment via distributed camera network and privacy-preserving edge computing
INTRODUCTION: Mild cognitive impairment (MCI) is characterized by a decline in cognitive functions beyond typical age and education-related expectations. Since, MCI has been linked to reduced social interactions and incr…
Edge-computingPrivacy PreservingA Secure and Lightweight NDN-Based Vehicular Network Using Edge Computing and Certificateless Signcryption
Named data networking (NDN), which is an implementation of information-centric networking (ICN), has emerged as a promising new direction in networking as a result of the shortcomings of the transmission control protocol…
Edge-computingHeterogeneity: An Open Challenge for Federated On-board Machine Learning
The design of satellite missions is currently undergoing a paradigm shift from the historical approach of individualised monolithic satellites towards distributed mission configurations, consisting of multiple small sate…
Distributed ComputingEdge-computingFederated LearningDeepAir: A Multi-Agent Deep Reinforcement Learning Based Scheme for an Unknown User Location Problem
The deployment of unmanned aerial vehicles (UAVs) in many different settings has provided various solutions and strategies for networking paradigms. Therefore, it reduces the complexity of the developments for the existi…
Deep Reinforcement LearningEdge-computing