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Edge Intelligence: Concepts, Architectures, Applications, and Future Directions
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-05677-3_16openalex-snapshot
Systolic Array Based Accelerator and Algorithm Mapping for Deep Learning Algorithms
inferredcites →https://doi.org/10.1007/978-3-030-45691-7_4openalex-snapshot
A Survey of AI Accelerators for Edge Environment
inferredcites →https://doi.org/10.1007/978-3-319-39595-1_14openalex-snapshot
Smart Agents and Fog Computing for Smart City Applications
inferredcites →https://doi.org/10.1007/978-3-319-93491-4_2openalex-snapshot
The Role of Mobile Edge Computing Towards Assisting IoT with Distributed Intelligence: A SmartLiving Perspective
inferredcites →https://doi.org/10.1007/978-3-319-99061-3_2openalex-snapshot
Optimization in Edge Computing and Small-Cell Networks
inferredcites →https://doi.org/10.1007/978-3-319-99061-3_4openalex-snapshot
Taxonomy of Edge Computing: Challenges, Opportunities, and Data Reduction Methods
inferredcites →https://doi.org/10.1007/s11036-020-01624-1openalex-snapshot
Vehicular Edge Computing and Networking: A Survey
inferredcites →https://doi.org/10.1007/s11277-021-08088-wopenalex-snapshot
A Novel Hybrid Optimization for Cluster‐Based Routing Protocol in Information-Centric Wireless Sensor Networks for IoT Based Mobile Edge Computing
inferredcites →https://doi.org/10.1007/s11831-019-09344-wopenalex-snapshot
A Survey of Deep Learning and Its Applications: A New Paradigm to Machine Learning
inferredcites →https://doi.org/10.1007/s13369-020-04493-8openalex-snapshot
Blockchain Powered Secure Range-Free Localization in Wireless Sensor Networks
inferredcites →https://doi.org/10.1007/s13748-012-0035-5openalex-snapshot
A survey of methods for distributed machine learning
inferredcites →https://doi.org/10.1016/j.adhoc.2019.102022openalex-snapshot
A hybrid secure routing and monitoring mechanism in IoT-based wireless sensor networks
inferredcites →https://doi.org/10.1016/j.csda.2011.06.006openalex-snapshot
An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets
inferredcites →https://doi.org/10.1016/j.dcan.2019.08.006openalex-snapshot
A survey of edge computing-based designs for IoT security
inferredcites →https://doi.org/10.1016/j.future.2017.02.014openalex-snapshot
Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach
inferredcites →https://doi.org/10.1016/j.future.2018.03.003openalex-snapshot
Building edge intelligence for online activity recognition in service-oriented IoT systems
inferredcites →https://doi.org/10.1016/j.future.2019.02.050openalex-snapshot
Edge computing: A survey
inferredcites →https://doi.org/10.1016/j.future.2019.04.016openalex-snapshot
A review of edge computing reference architectures and a new global edge proposal
inferredcites →https://doi.org/10.1016/j.iot.2019.100054openalex-snapshot
Modeling and evaluating a complex edge computing based systems: An emergency management support system case study
inferredcites →https://doi.org/10.1016/j.jnca.2019.05.005openalex-snapshot
Edge computing for Internet of Things: A survey, e-healthcare case study and future direction
inferredcites →https://doi.org/10.1016/j.jpdc.2018.08.009openalex-snapshot
Edge computing framework for enabling situation awareness in IoT based smart city
inferredcites →https://doi.org/10.1016/j.neucom.2018.11.002openalex-snapshot
Distributed optimization for deep learning with gossip exchange
inferredcites →https://doi.org/10.1080/14432471.2019.1623158openalex-snapshot
Henderson byte: Georg Ohm
inferredcites →https://doi.org/10.1109/access.2017.2778504openalex-snapshot
A Survey on the Edge Computing for the Internet of Things
inferredcites →https://doi.org/10.1109/access.2018.2866491openalex-snapshot
Fog Computing: Survey of Trends, Architectures, Requirements, and Research Directions
inferredcites →https://doi.org/10.1109/access.2019.2938236openalex-snapshot
Short-Term Traffic Prediction by Two-Level Data Driven Model in 5G-Enabled Edge Computing Networks
inferredcites →https://doi.org/10.1109/access.2019.2953172openalex-snapshot
Device-Enhanced MEC: Multi-Access Edge Computing (MEC) Aided by End Device Computation and Caching: A Survey
inferredcites →https://doi.org/10.1109/access.2020.3001277openalex-snapshot
A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art
inferredcites →https://doi.org/10.1109/access.2021.3050155openalex-snapshot
Cloud-Native Network Slicing Using Software Defined Networking Based Multi-Access Edge Computing: A Survey
inferredcites →https://doi.org/10.1109/aicas.2019.8771536openalex-snapshot
NeuroPilot: A Cross-Platform Framework for Edge-AI
inferredcites →https://doi.org/10.1109/apnoms.2015.7275447openalex-snapshot
A shared parking model in vehicular network using fog and cloud environment
inferredcites →https://doi.org/10.1109/asap.2018.8445118openalex-snapshot
Edge Intelligence: Challenges and Opportunities of Near-Sensor Machine Learning Applications
inferredcites →https://doi.org/10.1109/bigdata.2017.8258272openalex-snapshot
Edge computing architecture for applying AI to IoT
inferredcites →https://doi.org/10.1109/ccbd.2015.54openalex-snapshot
A Survey of Cloudlet Based Mobile Computing
inferredcites →https://doi.org/10.1109/ccece47787.2020.9255739openalex-snapshot
Novel Casestudy and Benchmarking of AlexNet for Edge AI: From CPU and GPU to FPGA
inferredcites →https://doi.org/10.1109/ccgrid.2015.114openalex-snapshot
A Deep Learning Prediction Process Accelerator Based FPGA
inferredcites →https://doi.org/10.1109/cloudnet.2017.8071529openalex-snapshot
PiCasso: A lightweight edge computing platform
inferredcites →https://doi.org/10.1109/comst.2018.2844341openalex-snapshot
Deep Learning for IoT Big Data and Streaming Analytics: A Survey
inferredcites →https://doi.org/10.1109/comst.2020.2970550openalex-snapshot
Convergence of Edge Computing and Deep Learning: A Comprehensive Survey
inferredcites →https://doi.org/10.1109/cvpr.2005.177openalex-snapshot
Histograms of Oriented Gradients for Human Detection
inferredcites →https://doi.org/10.1109/dcc.2019.00075openalex-snapshot
Accelerating Convolutional Neural Networks with Dynamic Channel Pruning
inferredcites →https://doi.org/10.1109/eit.2015.7293374openalex-snapshot
A survey on smart grid metering infrastructures: Threats and solutions
inferredcites →https://doi.org/10.1109/fmec.2017.7946409openalex-snapshot
Cloud, fog and edge: Cooperation for the future?
inferredcites →https://doi.org/10.1109/hpca.2019.00048openalex-snapshot
Machine Learning at Facebook: Understanding Inference at the Edge
inferredcites →https://doi.org/10.1109/hpca47549.2020.00027openalex-snapshot
PREMA: A Predictive Multi-Task Scheduling Algorithm For Preemptible Neural Processing Units
inferredcites →https://doi.org/10.1109/icaem.2019.8853780openalex-snapshot
Artificial Intelligence/ Machine Learning in IoT for Authentication and Authorization of Edge Devices
inferredcites →https://doi.org/10.1109/iccc.2018.00010openalex-snapshot
An Edge Based Smart Parking Solution Using Camera Networks and Deep Learning
inferredcites →https://doi.org/10.1109/icccas.2010.5581983openalex-snapshot
Preceding vehicle detection using Histograms of Oriented Gradients
inferredcites →https://doi.org/10.1109/iccv.2013.257openalex-snapshot
Joint Deep Learning for Pedestrian Detection
inferredcites →https://doi.org/10.1109/icdcs.2019.00170openalex-snapshot
Machine Learning + Distributed IoT = Edge Intelligence
inferredcites →https://doi.org/10.1109/icdcs.2019.00182openalex-snapshot
OpenEI: An Open Framework for Edge Intelligence
inferredcites →https://doi.org/10.1109/ie.2014.54openalex-snapshot
Augmented Brain Computer Interaction Based on Fog Computing and Linked Data
inferredcites →https://doi.org/10.1109/infocom.2018.8486403openalex-snapshot
When Edge Meets Learning: Adaptive Control for Resource-Constrained Distributed Machine Learning
inferredcites →https://doi.org/10.1109/isco.2016.7727082openalex-snapshot
A survey on mobile edge computing
inferredcites →https://doi.org/10.1109/isorc.2017.23openalex-snapshot
Short Paper: Towards Low-Cost Indoor Localization Using Edge Computing Resources
inferredcites →https://doi.org/10.1109/isorc.2018.00021openalex-snapshot
An Edge Computing Architecture in the Internet of Things
inferredcites →https://doi.org/10.1109/ispdc.2019.000-4openalex-snapshot
Machine Learning Model Updates in Edge Computing: An Optimal Stopping Theory Approach
inferredcites →https://doi.org/10.1109/jiot.2016.2579198openalex-snapshot
Edge Computing: Vision and Challenges
inferredcites →https://doi.org/10.1109/jiot.2020.2984887openalex-snapshot
Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence
inferredcites →https://doi.org/10.1109/jiot.2020.3001218openalex-snapshot
Offloading Autonomous Driving Services via Edge Computing
inferredcites →https://doi.org/10.1109/jproc.2019.2895553openalex-snapshot
Adaptable and Data-Driven Softwarized Networks: Review, Opportunities, and Challenges
inferredcites →https://doi.org/10.1109/jproc.2019.2915983openalex-snapshot
Edge Computing for Autonomous Driving: Opportunities and Challenges
inferredcites →https://doi.org/10.1109/jproc.2019.2918951openalex-snapshot
Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computing
inferredcites →https://doi.org/10.1109/jproc.2019.2921977openalex-snapshot
Deep Learning With Edge Computing: A Review
inferredcites →https://doi.org/10.1109/jssc.2017.2778281openalex-snapshot
A High Energy Efficient Reconfigurable Hybrid Neural Network Processor for Deep Learning Applications
inferredcites →https://doi.org/10.1109/mc.2017.3641638openalex-snapshot
Real-Time Video Analytics: The Killer App for Edge Computing
inferredcites →https://doi.org/10.1109/mce.2016.2590118openalex-snapshot
Mobile-Edge Computing Architecture: The role of MEC in the Internet of Things
inferredcites →https://doi.org/10.1109/mci.2018.2840738openalex-snapshot
Recent Trends in Deep Learning Based Natural Language Processing [Review Article]
inferredcites →https://doi.org/10.1109/mcom.2018.1700817openalex-snapshot
Medical Image Forgery Detection for Smart Healthcare
inferredcites →https://doi.org/10.1109/mnet.2017.1700030openalex-snapshot
Serving at the Edge: A Scalable IoT Architecture Based on Transparent Computing
inferredcites →https://doi.org/10.1109/mnet.2018.1700344openalex-snapshot
Blockchain-Enabled Security in Electric Vehicles Cloud and Edge Computing
inferredcites →https://doi.org/10.1109/mnet.2019.1800235openalex-snapshot
Smart-Edge-CoCaCo: AI-Enabled Smart Edge with Joint Computation, Caching, and Communication in Heterogeneous IoT
inferredcites →https://doi.org/10.1109/mnet.2019.1800254openalex-snapshot
Intelligent Edge Computing for IoT-Based Energy Management in Smart Cities
inferredcites →https://doi.org/10.1109/mnet.2019.1800286openalex-snapshot
In-Edge AI: Intelligentizing Mobile Edge Computing, Caching and Communication by Federated Learning
inferredcites →https://doi.org/10.1109/mobilecloud.2016.16openalex-snapshot
Mobile Edge Computing: Progress and Challenges
inferredcites →https://doi.org/10.1109/nas.2015.7255196openalex-snapshot
FAST: A fog computing assisted distributed analytics system to monitor fall for stroke mitigation
inferredcites →https://doi.org/10.1109/padsw.2018.8645013openalex-snapshot
JALAD: Joint Accuracy-And Latency-Aware Deep Structure Decoupling for Edge-Cloud Execution
inferredcites →https://doi.org/10.1109/sec.2016.25openalex-snapshot
Poster Abstract: Smart Urban Surveillance Using Fog Computing
inferredcites →https://doi.org/10.1109/sec.2016.38openalex-snapshot
DeepCham: Collaborative Edge-Mediated Adaptive Deep Learning for Mobile Object Recognition
inferredcites →https://doi.org/10.1109/sec.2018.00016openalex-snapshot
VideoEdge: Processing Camera Streams using Hierarchical Clusters
inferredcites →https://doi.org/10.1109/tcad.2018.2858384openalex-snapshot
DeepThings: Distributed Adaptive Deep Learning Inference on Resource-Constrained IoT Edge Clusters
inferredcites →https://doi.org/10.1109/tcsi.2011.2161360openalex-snapshot
Neural Synaptic Weighting With a Pulse-Based Memristor Circuit
inferredcites →https://doi.org/10.1109/tcsi.2017.2735490openalex-snapshot
A Reconfigurable Streaming Deep Convolutional Neural Network Accelerator for Internet of Things
inferredcites →https://doi.org/10.1109/tie.2014.2356439openalex-snapshot
Neuromorphic Hardware System for Visual Pattern Recognition With Memristor Array and CMOS Neuron
inferredcites →https://doi.org/10.1109/tii.2019.2902878openalex-snapshot
Artificial Intelligence-Driven Mechanism for Edge Computing-Based Industrial Applications
inferredcites →https://doi.org/10.1109/tii.2019.2915592openalex-snapshot
Edge Intelligence-Assisted Smoke Detection in Foggy Surveillance Environments
inferredcites →https://doi.org/10.1109/tit.1967.1053964openalex-snapshot
Nearest neighbor pattern classification
inferredcites →https://doi.org/10.1109/tmc.2020.2999956openalex-snapshot
AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles
inferredcites →https://doi.org/10.1109/twc.2019.2946140openalex-snapshot
Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing
inferredcites →https://doi.org/10.1109/vlsi-dat.2018.8373244openalex-snapshot
Techology trend of edge AI
inferredcites →https://doi.org/10.1109/vlsi-dat.2019.8741613openalex-snapshot
Heterogeneous Computing for Edge AI
inferredcites →https://doi.org/10.1109/wcnc.2018.8377192openalex-snapshot
Ultra-low latency cloud-fog computing for industrial Internet of Things
inferredcites →https://doi.org/10.1109/wf-iot.2019.8767231openalex-snapshot
Efficient Deployment of Predictive Analytics in Edge Gateways: Fall Detection Scenario
inferredcites →https://doi.org/10.1117/12.2518469openalex-snapshot
Deep learning on mobile devices: a review
inferredcites →https://doi.org/10.1145/2462456.2464451openalex-snapshot
Just-in-time provisioning for cyber foraging
inferredcites →https://doi.org/10.1145/2594368.2594383openalex-snapshot
Towards wearable cognitive assistance
inferredcites →https://doi.org/10.1145/2619287.2619295openalex-snapshot
In-network cache simulations based on a YouTube traffic analysis at the edge network
inferredcites →https://doi.org/10.1145/2789168.2790123openalex-snapshot
The Design and Implementation of a Wireless Video Surveillance System
inferredcites →https://doi.org/10.1145/2847263.2847265openalex-snapshot
Going Deeper with Embedded FPGA Platform for Convolutional Neural Network
inferredcites →https://doi.org/10.1145/2989275.2989286openalex-snapshot
On Developing Smart Transportation Applications in Fog Computing Paradigm
inferredcites →https://doi.org/10.1145/2994551.2994564openalex-snapshot
Sparsification and Separation of Deep Learning Layers for Constrained Resource Inference on Wearables
inferredcites →https://doi.org/10.1145/3061639.3062207openalex-snapshot
Automated Systolic Array Architecture Synthesis for High Throughput CNN Inference on FPGAs
inferredcites →https://doi.org/10.1145/3097895.3097896openalex-snapshot
Characterization of 360-degree Videos
inferredcites →https://doi.org/10.1145/3213344.3213348openalex-snapshot
A Multi-Cloudlet Infrastructure for Future Smart Cities
inferredcites →https://doi.org/10.1145/3229625.3229629openalex-snapshot
Predictive View Generation to Enable Mobile 360-degree and VR Experiences
inferredcites →https://doi.org/10.1145/3300061.3300116openalex-snapshot
Edge Assisted Real-time Object Detection for Mobile Augmented Reality
inferredcites →https://doi.org/10.1145/3304103openalex-snapshot
Spiking Neural Networks Hardware Implementations and Challenges
inferredcites →https://doi.org/10.1145/3314221.3314597openalex-snapshot
Compiling KB-sized machine learning models to tiny IoT devices
inferredcites →https://doi.org/10.1145/863955.863957openalex-snapshot
A knowledge plane for the internet
inferredcites →https://doi.org/10.1364/ofc.2019.tu2e.1openalex-snapshot
On-board Artificial Intelligence based on Edge Computing in Optical Transport Networks
inferredcites →https://doi.org/10.23919/vlsic.2017.8008534openalex-snapshot
A 1.06-to-5.09 TOPS/W reconfigurable hybrid-neural-network processor for deep learning applications
inferredcites →https://doi.org/10.3389/fnins.2019.00260openalex-snapshot
Demonstrating Advantages of Neuromorphic Computation: A Pilot Study
inferredcites →https://doi.org/10.3390/electronics8060661openalex-snapshot
A Review of Binarized Neural Networks
inferredcites →https://doi.org/10.3390/s17010018openalex-snapshot
A Machine Learning Approach to Pedestrian Detection for Autonomous Vehicles Using High-Definition 3D Range Data
inferredcites →https://doi.org/10.3390/s19153353openalex-snapshot
Edge Computing, IoT and Social Computing in Smart Energy Scenarios
inferredcites →https://doi.org/10.48550/arxiv.1207.4676openalex-snapshot
Proceedings of the 29th International Conference on Machine Learning (ICML-12)
inferredcites →https://doi.org/10.48550/arxiv.1503.02531openalex-snapshot
Distilling the Knowledge in a Neural Network
inferredcites →https://doi.org/10.48550/arxiv.1602.04283openalex-snapshot
Deep Learning on FPGAs: Past, Present, and Future
inferredcites →https://doi.org/10.48550/arxiv.1609.08144openalex-snapshot
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
inferredcites →https://doi.org/10.48550/arxiv.1611.01942openalex-snapshot
DeepSense: A Unified Deep Learning Framework for Time-Series Mobile Sensing Data Processing
inferredcites →https://doi.org/10.48550/arxiv.1803.05880openalex-snapshot
GossipGraD: Scalable Deep Learning using Gossip Communication based Asynchronous Gradient Descent
inferredcites →https://doi.org/10.48550/arxiv.1808.04456openalex-snapshot
Multimodal Deep Neural Networks using Both Engineered and Learned Representations for Biodegradability Prediction
inferredcites →https://doi.org/10.48550/arxiv.1901.02358openalex-snapshot
FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network
inferredcites →https://doi.org/10.48550/arxiv.1902.01046openalex-snapshot
Towards Federated Learning at Scale: System Design
inferredcites →https://doi.org/10.48550/arxiv.1906.01878openalex-snapshot
pCAMP: Performance Comparison of Machine Learning Packages on the Edges
inferredcites →https://doi.org/10.48550/arxiv.2102.01341openalex-snapshot
Benchmarking Quantized Neural Networks on FPGAs with FINN
inferredcites →https://doi.org/10.48550/arxiv.2103.12166openalex-snapshot
Special Session: Reliability Analysis for ML/AI Hardware
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Tiny Machine Learning for Enhanced Edge Intelligence
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Research on Intelligent Perception and Inference Mechanisms for Embedded Virtualization in Edge Devices Under Heterogeneous Computing
inferred← citeshttps://doi.org/10.1109/iccit65724.2025.11167704openalex-snapshot
Social Media Analytics Using AI-Enhanced Edge-Fog Computing
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Edge-Deployed Deep Learning Based Vision System for Real-Time Object Sorting
inferred← citeshttps://doi.org/10.1109/icicit69063.2026.11633933openalex-snapshot
Edge–Cloud Collaborative Deep Learning Framework for Real-Time IoT Analytics
inferred← citeshttps://doi.org/10.1109/icitsif69060.2026.11609177openalex-snapshot
Adaptive Edge Intelligence for Sustainable IoT-Based Smart City Infrastructure
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Dynamic Model and Node Selection for Collaborative Inference of Large/Small Models in Vehicular Networks
inferred← citeshttps://doi.org/10.1109/ijcnn64981.2025.11227243openalex-snapshot
ApproXAI: Energy-Efficient Hardware Acceleration of Explainable AI using Approximate Computing
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Serverless Microservice Architecture for Cloud-Edge Intelligence in Sensor Networks
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Artificial Intelligence Techniques for Resilient and Trustworthy V2X Communications
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A Review of Heterogeneous Network Convergence Technology and Development Trends
inferred← citeshttps://doi.org/10.1109/sera61261.2024.10685647openalex-snapshot
Leveraging Shared Accelerators in Kubernetes Clusters with rOpenCL
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Edge Intelligence: A Deep Distilled Model for Wearables to Enable Proactive Eldercare
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Lightweight Federated Learning for Terminal-Edge-Cloud With Two-Step Privacy Protection in Consumer Electronics
inferred← citeshttps://doi.org/10.1109/tetc.2023.3297066openalex-snapshot
An Edge-Cloud Collaboration Framework for Graph Processing in Smart Society
inferred← citeshttps://doi.org/10.1109/tmc.2025.3546910openalex-snapshot
Privacy Preservation Strategies for Malware-Infected Edge Intelligence Systems: A Bayesian Stochastic Game-Based Approach
inferred← citeshttps://doi.org/10.1109/tmc.2025.3566492openalex-snapshot
Trusted Clustering Based Federated Learning in Edge Networks
inferred← citeshttps://doi.org/10.1109/tmc.2025.3615667openalex-snapshot
Dynamic Optimization of Edge Aggregation Structures and Update Frequencies for Efficient Distributed Hierarchical Model Training
inferred← citeshttps://doi.org/10.1109/tmc.2026.3700660openalex-snapshot
Lyapunov-Guided Latency Optimization in Semantic Communication Empowered Edge Networks
inferred← citeshttps://doi.org/10.1109/tsc.2025.3586152openalex-snapshot
Integrating IoT and 6G: Applications of Edge Intelligence, Challenges, and Future Directions
inferred← citeshttps://doi.org/10.1109/tsc.2025.3592421openalex-snapshot
The Wonderful Flower of Seven Colors: Self-Evolution Approach for Multi-Terminal Personalized Service Processing
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Optimising the computational and cost efficiency of hierarchical federated edge learning
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Opportunistic Digital Twin: an Edge Intelligence enabler for Smart City
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Multi-Compression Scale DNN Inference Acceleration based on Cloud-Edge-End Collaboration
inferred← citeshttps://doi.org/10.1145/3749531openalex-snapshot
WSCoach: Wearable Real-time Auditory Feedback for Reducing Unwanted Words in Daily Communication
inferred← citeshttps://doi.org/10.1515/itit-2023-0001openalex-snapshot
A framework for AI-based self-adaptive cyber-physical process systems
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Advanced Implementation of DNN Translator using ResNet9 for Edge Devices
inferred← citeshttps://doi.org/10.2139/ssrn.7075188openalex-snapshot
Edge-Enabled Digital twin-Based Federated Explainable Agentic Artificial Intelligence for Real-Time Sustainable Smart City Governance
inferred← citeshttps://doi.org/10.2139/ssrn.7435408openalex-snapshot
Federated Membrane Learning for Heterogeneous Edge Intelligence: A Privacy-Preserving, Communication-Efficient Framework for Constrained Multi-Objective Optimization
inferred← citeshttps://doi.org/10.23919/indiacom70271.2026.11525542openalex-snapshot
The Rise of Edge Intelligence: AI Empowerment at the Network Frontier
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Edge Computing in IoT Networks: Enhancing Efficiency, Reducing Latency, and Improving Scalability.
inferred← citeshttps://doi.org/10.26599/tst.2024.9010140openalex-snapshot
Cooperative Digital Healthcare Task Scheduling and Resource Management in Edge Intelligence Systems
inferred← citeshttps://doi.org/10.30812/matrik.v23i3.3961openalex-snapshot
Deep Learning Model Compression Techniques Performance on Edge Devices
inferred← citeshttps://doi.org/10.30939/ijastech..1335390openalex-snapshot
Edge AI-Assisted IoV Application for Aggressive Driver Monitoring: A Case Study on Public Transport Buses
inferred← citeshttps://doi.org/10.32996/jcsts.2025.7.5.4openalex-snapshot
From Data Lakes to Data Fabric/Mesh: The Future of Enterprise Data Platforms in a Multi-Cloud World
inferred← citeshttps://doi.org/10.3389/fnins.2023.1154241openalex-snapshot
Trainable quantization for Speedy Spiking Neural Networks
inferred← citeshttps://doi.org/10.3390/app132413262openalex-snapshot
From Cyber–Physical Convergence to Digital Twins: A Review on Edge Computing Use Case Designs
inferred← citeshttps://doi.org/10.3390/bdcc7010044openalex-snapshot
Disclosing Edge Intelligence: A Systematic Meta-Survey
inferred← citeshttps://doi.org/10.3390/electronics12030685openalex-snapshot
Real-Time Finger-Writing Character Recognition via ToF Sensors on Edge Deep Learning
inferred← citeshttps://doi.org/10.3390/electronics15010196openalex-snapshot
Advances in Computational Intelligence and Machine Learning Models and Applications
inferred← citeshttps://doi.org/10.3390/electronics15112351openalex-snapshot
Connectivity Assessment: Strength, Trend, and Regularity in Opportunistic Networks
inferred← citeshttps://doi.org/10.3390/fi17040175openalex-snapshot
A Survey on Edge Computing (EC) Security Challenges: Classification, Threats, and Mitigation Strategies
inferred← citeshttps://doi.org/10.3390/fi17090417openalex-snapshot
Intelligent Edge Computing and Machine Learning: A Survey of Optimization and Applications
inferred← citeshttps://doi.org/10.3390/fi17110494openalex-snapshot
MEC and SDN Enabling Technologies, Design Challenges, and Future Directions of Tactile Internet and Immersive Communications
inferred← citeshttps://doi.org/10.3390/ijgi13120445openalex-snapshot
A 3D Model-Based Framework for Real-Time Emergency Evacuation Using GIS and IoT Devices
inferred← citeshttps://doi.org/10.3390/s23041963openalex-snapshot
Autonomous Vehicles Enabled by the Integration of IoT, Edge Intelligence, 5G, and Blockchain
inferred← citeshttps://doi.org/10.3390/s25061687openalex-snapshot
Hand Gesture Recognition on Edge Devices: Sensor Technologies, Algorithms, and Processing Hardware
inferred← citeshttps://doi.org/10.3390/su16167039openalex-snapshot
The Role of 6G Technologies in Advancing Smart City Applications: Opportunities and Challenges
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Exploring Computing Paradigms for Electric Vehicles: From Cloud to Edge Intelligence, Challenges and Future Directions
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Vision-Language Models on Edge Devices
inferred← citeshttps://doi.org/10.4018/979-8-3373-1489-1.ch016openalex-snapshot
The Role of Artificial Intelligence in Shaping the Future of Cloud Kitchens
inferred← citeshttps://doi.org/10.4018/979-8-3373-2125-7.ch004openalex-snapshot
Edge Intelligence Expanding BI Architectures Beyond the Cloud
inferred← citeshttps://doi.org/10.47852/bonviewaia3202689openalex-snapshot
A Critical Historic Overview of Artificial Intelligence: Issues, Challenges, Opportunities, and Threats
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A Hybrid Genetic-Reinforcement Learning Framework for Edge-Enabled Social IoT
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DATA SCIENCE IN ENERGY CONSUMPTION ANALYSIS: A REVIEW OF AI TECHNIQUES IN IDENTIFYING PATTERNS AND EFFICIENCY OPPORTUNITIES
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Dynamic Object Detection in Surveillance Videos using Temporal Convolutional Networks and Federated Learning in Edge Computing Environments
inferred← citeshttps://doi.org/10.61927/igmin183openalex-snapshot
New Scientific Field for Modelling Complex Dynamical Systems: The Cybernetics Artificial Intelligence (CAI)
inferred← citeshttps://doi.org/10.7717/peerj-cs.2306openalex-snapshot
RT-Cabi: an Internet of Things based framework for anomaly behavior detection with data correction through edge collaboration and dynamic feature fusion
inferred← citeshttps://doi.org/10.7717/peerj-cs.3503openalex-snapshot
Hybrid 3D modelling framework for indoor navigation using federated learning and Internet of Things-enabled edge devices
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