Papers Edge-computing
“Edge-computing” 태그가 달린 논문 1,279편 · 필터 해제
DFDT: Dynamic Fast Decision Tree for IoT Data Stream Mining on Edge Devices
The Internet of Things generates massive data streams, with edge computing emerging as a key enabler for online IoT applications and 5G networks. Edge solutions facilitate real-time machine learning inference, but also r…
Edge-computingInTec: integrated things-edge computing: a framework for distributing machine learning pipelines in edge AI systems
With the rapid expansion of the Internet of Things (IoT), sensors, smartphones, and wearables have become integral to daily life, powering smart applications in home automation, healthcare, and intelligent transportation…
Cloud ComputingEdge-computingMotion DetectionPulmonary Tuberculosis Edge Diagnosis System Based on MindSpore Framework: Low-cost and High-precision Implementation with Ascend 310 Chip
Pulmonary Tuberculosis (PTB) remains a major challenge for global health, especially in areas with poor medical resources, where access to specialized medical knowledge and diagnostic tools is limited. This paper present…
DiagnosticEdge-computingA Hybrid Edge Classifier: Combining TinyML-Optimised CNN with RRAM-CMOS ACAM for Energy-Efficient Inference
In recent years, the development of smart edge computing systems to process information locally is on the rise. Many near-sensor machine learning (ML) approaches have been implemented to introduce accurate and energy eff…
Edge-computingTemplate MatchingSmartEdge: Smart Healthcare End-to-End Integrated Edge and Cloud Computing System for Diabetes Prediction Enabled by Ensemble Machine Learning
The Internet of Things (IoT) revolutionizes smart city domains such as healthcare, transportation, industry, and education. The Internet of Medical Things (IoMT) is gaining prominence, particularly in smart hospitals and…
Cloud ComputingDiabetes PredictionEdge-computingPrediction+1AT-Drone: Benchmarking Adaptive Teaming in Multi-Drone Pursuit
Adaptive teaming-the capability of agents to effectively collaborate with unfamiliar teammates without prior coordination-is widely explored in virtual video games but overlooked in real-world multi-robot contexts. Yet, …
BenchmarkingEdge-computingFedMHO: Heterogeneous One-Shot Federated Learning Towards Resource-Constrained Edge Devices
Federated Learning (FL) is increasingly adopted in edge computing scenarios, where a large number of heterogeneous clients operate under constrained or sufficient resources. The iterative training process in conventional…
Edge-computingFederated LearningGenerative AI-Enhanced Cooperative MEC of UAVs and Ground Stations for Unmanned Surface Vehicles
The increasing deployment of unmanned surface vehicles (USVs) require computational support and coverage in applications such as maritime search and rescue. Unmanned aerial vehicles (UAVs) can offer low-cost, flexible ae…
Edge-computingMulti-agent Reinforcement LearningExploring Neural Network Pruning with Screening Methods
Deep neural networks (DNNs) such as convolutional neural networks (CNNs) for visual tasks, recurrent neural networks (RNNs) for sequence data, and transformer models for rich linguistic or multimodal tasks, achieved unpr…
Edge-computingNetwork PruningUAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning
Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) and data collection (DC) have been popular research issues. Different from existing works that consider MEC and DC scenarios separately, this paper inves…
Deep Reinforcement LearningEdge-computingIntelligent Offloading in Vehicular Edge Computing: A Comprehensive Review of Deep Reinforcement Learning Approaches and Architectures
The increasing complexity of Intelligent Transportation Systems (ITS) has led to significant interest in computational offloading to external infrastructures such as edge servers, vehicular nodes, and UAVs. These dynamic…
Decision MakingDeep Reinforcement LearningEdge-computingFairness+3A Survey on Video Analytics in Cloud-Edge-Terminal Collaborative Systems
The explosive growth of video data has driven the development of distributed video analytics in cloud-edge-terminal collaborative (CETC) systems, enabling efficient video processing, real-time inference, and privacy-pres…
Autonomous DrivingEdge-computingPrivacy PreservingScheduling+1Graph Federated Learning Based Proactive Content Caching in Edge Computing
With the rapid growth of mobile data traffic and the increasing prevalence of video streaming, proactive content caching in edge computing has become crucial for reducing latency and alleviating network congestion. Howev…
Edge-computingFederated LearningIntelligent Sensing-to-Action for Robust Autonomy at the Edge: Opportunities and Challenges
Autonomous edge computing in robotics, smart cities, and autonomous vehicles relies on the seamless integration of sensing, processing, and actuation for real-time decision-making in dynamic environments. At its core is …
Autonomous VehiclesEdge-computingKHAIT: K-9 Handler Artificial Intelligence Teaming for Collaborative Sensemaking
In urban search and rescue (USAR) operations, communication between handlers and specially trained canines is crucial but often complicated by challenging environments and the specific behaviors canines are trained to ex…
Edge-computingobject-detectionObject DetectionThe M-factor: A Novel Metric for Evaluating Neural Architecture Search in Resource-Constrained Environments
Neural Architecture Search (NAS) aims to automate the design of deep neural networks. However, existing NAS techniques often focus on maximising accuracy, neglecting model efficiency. This limitation restricts their use …
Edge-computingNeural Architecture Searchreinforcement-learningReinforcement LearningSWIFT: Mapping Sub-series with Wavelet Decomposition Improves Time Series Forecasting
In recent work on time-series prediction, Transformers and even large language models have garnered significant attention due to their strong capabilities in sequence modeling. However, in practical deployments, time-ser…
Edge-computingTime SeriesTime Series ForecastingTime Series PredictionVehicular Multi-Tier Distributed Computing with Hybrid THz-RF Transmission in Satellite-Terrestrial Integrated Networks
In this paper, we propose a Satellite-Terrestrial Integrated Network (STIN) assisted vehicular multi-tier distributed computing (VMDC) system leveraging hybrid terahertz (THz) and radio frequency (RF) communication techn…
Distributed ComputingEdge-computingEnhancing Disaster Resilience with UAV-Assisted Edge Computing: A Reinforcement Learning Approach to Managing Heterogeneous Edge Devices
Edge sensing and computing is rapidly becoming part of intelligent infrastructure architecture leading to operational reliance on such systems in disaster or emergency situations. In such scenarios there is a high chance…
Edge-computingBringing RGB and IR Together: Hierarchical Multi-Modal Enhancement for Robust Transmission Line Detection
Ensuring a stable power supply in rural areas relies heavily on effective inspection of power equipment, particularly transmission lines (TLs). However, detecting TLs from aerial imagery can be challenging when dealing w…
Edge-computingLine Detection