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Artificial Intelligence (AI) and Machine Learning for Multimedia and Edge Information Processing
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Explainable AI: Interpreting, Explaining and Visualizing Deep Learning
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Learning Structures Through Reinforcement
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Edge computing-based person detection system for top view surveillance: Using CenterNet with transfer learning
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Big Sensor Data Applications in Urban Environments
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AI-enabled mobile multimedia service instance placement scheme in mobile edge computing
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DroneCOCoNet: Learning-based edge computation offloading and control networking for drone video analytics
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A Survey on Object Detection for the Internet of Multimedia Things (IoMT) using Deep Learning and Event-based Middleware: Approaches, Challenges, and Future Directions
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Emotion recognition using deep learning approach from audio–visual emotional big data
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Privacy-preserving federated k-means for proactive caching in next generation cellular networks
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Highly-efficient fog-based deep learning AAL fall detection system
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Applying machine learning techniques for caching in next-generation edge networks: A comprehensive survey
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A deep genetic algorithm for human activity recognition leveraging fog computing frameworks
inferredcites →https://doi.org/10.1016/j.scs.2018.01.053openalex-snapshot
Towards sustainable smart cities: A review of trends, architectures, components, and open challenges in smart cities
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Light-weight AI and IoT collaboration for surveillance video pre-processing
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A high-speed and high-precision Winner-Select-Output (WSO) ASIC
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Edge Caching at Base Stations With Device-to-Device Offloading
inferredcites →https://doi.org/10.1109/access.2017.2779939openalex-snapshot
LSTM Fully Convolutional Networks for Time Series Classification
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UbeHealth: A Personalized Ubiquitous Cloud and Edge-Enabled Networked Healthcare System for Smart Cities
inferredcites →https://doi.org/10.1109/access.2018.2884913openalex-snapshot
DeepMEC: Mobile Edge Caching Using Deep Learning
inferredcites →https://doi.org/10.1109/access.2019.2925019openalex-snapshot
A Deep Reinforcement Learning Approach to Proactive Content Pushing and Recommendation for Mobile Users
inferredcites →https://doi.org/10.1109/access.2019.2947067openalex-snapshot
Toward Edge-Assisted Video Content Intelligent Caching With Long Short-Term Memory Learning
inferredcites →https://doi.org/10.1109/access.2019.2951219openalex-snapshot
Deep-Q-Network-Based Multimedia Multi-Service QoS Optimization for Mobile Edge Computing Systems
inferredcites →https://doi.org/10.1109/access.2019.2960191openalex-snapshot
Deep Reinforcement Learning-Based Video Quality Selection and Radio Bearer Control for Mobile Edge Computing Supported Short Video Applications
inferredcites →https://doi.org/10.1109/access.2020.2971566openalex-snapshot
iSEC: An Optimized Deep Learning Model for Image Classification on Edge Computing
inferredcites →https://doi.org/10.1109/access.2021.3109904openalex-snapshot
Deep Edge Computing for Videos
inferredcites →https://doi.org/10.1109/bmsb49480.2020.9379443openalex-snapshot
DRL Driven Energy-efficient Resource Allocation for Multimedia Broadband Services in Mobile Edge Network
inferredcites →https://doi.org/10.1109/candar51075.2020.00039openalex-snapshot
An implementation methodology for Neural Network on a Low-end FPGA Board
inferredcites →https://doi.org/10.1109/cfec.2018.8358733openalex-snapshot
Edge Enhanced Deep Learning System for Large-Scale Video Stream Analytics
inferredcites →https://doi.org/10.1109/comst.2017.2745201openalex-snapshot
A Survey on Mobile Edge Computing: The Communication Perspective
inferredcites →https://doi.org/10.1109/cvpr.2019.00268openalex-snapshot
AE2-Nets: Autoencoder in Autoencoder Networks
inferredcites →https://doi.org/10.1109/edge.2018.00013openalex-snapshot
Are Existing Knowledge Transfer Techniques Effective for Deep Learning with Edge Devices?
inferredcites →https://doi.org/10.1109/fccm51124.2021.00046openalex-snapshot
Edge Accelerator for Lifelong Deep Learning using Streaming Linear Discriminant Analysis
inferredcites →https://doi.org/10.1109/hpec43674.2020.9286209openalex-snapshot
Architectural Analysis of Deep Learning on Edge Accelerators
inferredcites →https://doi.org/10.1109/i2ct51068.2021.9418124openalex-snapshot
Deep Learning Model for Image-Based Plant Diseases Detection on Edge Devices
inferredcites →https://doi.org/10.1109/icc42927.2021.9500902openalex-snapshot
Enabling Real-Time AI Edge Video Analytics
inferredcites →https://doi.org/10.1109/icce50685.2021.9427679openalex-snapshot
Challenges for Edge-AI Implementations of Text-To-Speech Synthesis
inferredcites →https://doi.org/10.1109/iccs.2018.8689227openalex-snapshot
Deep Learning Enabled Dynamic Reactive Video Caching in Mobile Edge Networks
inferredcites →https://doi.org/10.1109/iccworkshops50388.2021.9473669openalex-snapshot
Privacy Enhanced Speech Emotion Communication using Deep Learning Aided Edge Computing
inferredcites →https://doi.org/10.1109/icdcs.2019.00107openalex-snapshot
Data-driven Task Allocation for Multi-task Transfer Learning on the Edge
inferredcites →https://doi.org/10.1109/icengtechnol.2017.8308186openalex-snapshot
Understanding of a convolutional neural network
inferredcites →https://doi.org/10.1109/icimu49871.2020.9243367openalex-snapshot
Performance Analysis of Deep Neural Networks for Object Classification with Edge TPU
inferredcites →https://doi.org/10.1109/icme46284.2020.9102836openalex-snapshot
MA360: Multi-Agent Deep Reinforcement Learning Based Live 360-Degree Video Streaming on Edge
inferredcites →https://doi.org/10.1109/icoin48656.2020.9016591openalex-snapshot
Fast and Reliable Offloading via Deep Reinforcement Learning for Mobile Edge Video Computing
inferredcites →https://doi.org/10.1109/icoin50884.2021.9333920openalex-snapshot
Deep Regression Model for Videos Popularity Prediction in Mobile Edge Caching Networks
inferredcites →https://doi.org/10.1109/icpads47876.2019.00080openalex-snapshot
Enabling Adaptive Deep Neural Networks for Video Surveillance in Distributed Edge Clouds
inferredcites →https://doi.org/10.1109/icpads51040.2020.00044openalex-snapshot
Multi-user Edge-assisted Video Analytics Task Offloading Game based on Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/incit.2019.8912138openalex-snapshot
A Novel Hierarchical Edge Computing Solution Based on Deep Learning for Distributed Image Recognition in IoT Systems
inferredcites →https://doi.org/10.1109/indin45582.2020.9442166openalex-snapshot
Multitask Deep Learning for Edge Intelligence Video Surveillance System
inferredcites →https://doi.org/10.1109/infocom.2018.8485905openalex-snapshot
DeepDecision: A Mobile Deep Learning Framework for Edge Video Analytics
inferredcites →https://doi.org/10.1109/infocom41043.2020.9155284openalex-snapshot
SurveilEdge: Real-time Video Query based on Collaborative Cloud-Edge Deep Learning
inferredcites →https://doi.org/10.1109/iwcmc51323.2021.9498953openalex-snapshot
Research on the Application of 5G Cloud-network-edge-device Convergence and Intelligent Video Technology in Smart Grid
inferredcites →https://doi.org/10.1109/jiot.2017.2695535openalex-snapshot
Big Sensor Data Systems for Smart Cities
inferredcites →https://doi.org/10.1109/jiot.2020.2968941openalex-snapshot
Video Surveillance on Mobile Edge Networks—A Reinforcement-Learning-Based Approach
inferredcites →https://doi.org/10.1109/jiot.2020.3026354openalex-snapshot
Intelligent Resource Allocation for Video Analytics in Blockchain-Enabled Internet of Autonomous Vehicles With Edge Computing
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/jsen.2021.3061608openalex-snapshot
Deep Learning-Based Sign Language Digits Recognition From Thermal Images With Edge Computing System
inferredcites →https://doi.org/10.1109/jstars.2017.2747599openalex-snapshot
FusionNet: Edge Aware Deep Convolutional Networks for Semantic Segmentation of Remote Sensing Harbor Images
inferredcites →https://doi.org/10.1109/maes.2020.3043072openalex-snapshot
Artificial Intelligence and Data Fusion at the Edge
inferredcites →https://doi.org/10.1109/mc.2020.3034951openalex-snapshot
Edge Artificial Intelligence Chips for the Cyberphysical Systems Era
inferredcites →https://doi.org/10.1109/mcom.2017.1600514openalex-snapshot
Internet-of-Things-Based Smart Cities: Recent Advances and Challenges
inferredcites →https://doi.org/10.1109/mie.2020.3026837openalex-snapshot
Edge Artificial Intelligence for Industrial Internet of Things Applications: An Industrial Edge Intelligence Solution
inferredcites →https://doi.org/10.1109/mm.2018.112130359openalex-snapshot
Loihi: A Neuromorphic Manycore Processor with On-Chip Learning
inferredcites →https://doi.org/10.1109/msp.2017.2743240openalex-snapshot
Deep Reinforcement Learning: A Brief Survey
inferredcites →https://doi.org/10.1109/msp.2017.2765202openalex-snapshot
Generative Adversarial Networks: An Overview
inferredcites →https://doi.org/10.1109/mvt.2020.2979082openalex-snapshot
Predictive Voice-Over-Internet Protocol Fallback Over Vehicular Channels: Employing Artificial Intelligence at the Edge of 5G Networks
inferredcites →https://doi.org/10.1109/secon52354.2021.9491614openalex-snapshot
Deep Learning Video Analytics on Edge Computing Devices
inferredcites →https://doi.org/10.1109/smartcloud.2016.18openalex-snapshot
Challenges and Opportunities in Edge Computing
inferredcites →https://doi.org/10.1109/tcsvt.2021.3057872openalex-snapshot
Flow-Edge Guided Unsupervised Video Object Segmentation
inferredcites →https://doi.org/10.1109/tii.2019.2909473openalex-snapshot
Distributed Deep Learning Model for Intelligent Video Surveillance Systems with Edge Computing
inferredcites →https://doi.org/10.1109/tmc.2021.3105953openalex-snapshot
Deep Learning Video Analytics Through Edge Computing and Neural Processing Units on Mobile Devices
inferredcites →https://doi.org/10.1109/tmc.2021.3106147openalex-snapshot
Edge Intelligence for Adaptive Multimedia Streaming in Heterogeneous Internet of Vehicles
inferredcites →https://doi.org/10.1109/tmm.2021.3066050openalex-snapshot
Edge-Cloud Collaboration Enabled Video Service Enhancement: A Hybrid Human-Artificial Intelligence Scheme
inferredcites →https://doi.org/10.1109/tnet.2020.2979966openalex-snapshot
DeepCast: Towards Personalized QoE for Edge-Assisted Crowdcast With Deep Reinforcement Learning
inferredcites →https://doi.org/10.1109/tnse.2020.3038998openalex-snapshot
QoE-Aware 3D Video Streaming via Deep Reinforcement Learning in Software Defined Networking Enabled Mobile Edge Computing
inferredcites →https://doi.org/10.1109/tnse.2021.3083990openalex-snapshot
A Deep Learning Based Explainable Control System for Reconfigurable Networks of Edge Devices
inferredcites →https://doi.org/10.1109/tsp52935.2021.9522611openalex-snapshot
Offloading Deep Learning Empowered Image Segmentation from UAV to Edge Server
inferredcites →https://doi.org/10.1109/tvcg.2019.2934629openalex-snapshot
explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning
inferredcites →https://doi.org/10.1109/tvt.2019.2921615openalex-snapshot
Analysis and Optimization of Caching in Fog Radio Access Networks
inferredcites →https://doi.org/10.1109/tvt.2020.2973705openalex-snapshot
Deep Reinforcement Learning and Permissioned Blockchain for Content Caching in Vehicular Edge Computing and Networks
inferredcites →https://doi.org/10.1109/twc.2016.2636139openalex-snapshot
Context-Aware Proactive Content Caching With Service Differentiation in Wireless Networks
inferredcites →https://doi.org/10.1109/twc.2018.2806971openalex-snapshot
Content-Aware Proactive Caching for Backhaul Offloading in Cellular Network
inferredcites →https://doi.org/10.1109/twc.2019.2955129openalex-snapshot
Adaptive Video Streaming With Edge Caching and Video Transcoding Over Software-Defined Mobile Networks: A Deep Reinforcement Learning Approach
inferredcites →https://doi.org/10.1109/vtcfall.2019.8891508openalex-snapshot
A Deep Reinforcement Learning Based Content Caching and Mode Selection for Slice Instances in Fog Radio Access Networks
inferredcites →https://doi.org/10.1109/wcnc.2019.8885516openalex-snapshot
Deep Reinforcement Learning for Cooperative Edge Caching in Future Mobile Networks
inferredcites →https://doi.org/10.1109/wcnc.2019.8885803openalex-snapshot
Edge-assisted Adaptive Video Streaming with Deep Learning in Mobile Edge Networks
inferredcites →https://doi.org/10.1126/science.aaa8415openalex-snapshot
Machine learning: Trends, perspectives, and prospects
inferredcites →https://doi.org/10.1145/2342509.2342513openalex-snapshot
Fog computing and its role in the internet of things
inferredcites →https://doi.org/10.1364/ofc.2020.m3z.10openalex-snapshot
Remote Control of a Robot Rover Combining 5G, AI, and GPU Image Processing at the Edge
inferredcites →https://doi.org/10.1504/ijsnet.2012.045033openalex-snapshot
Low-memory video compression architecture using strip-based processing for implementation in wireless multimedia sensor networks
inferredcites →https://doi.org/10.26599/tst.2021.9010043openalex-snapshot
Memristor-based signal processing for edge computing
inferredcites →https://doi.org/10.3390/electronics10080895openalex-snapshot
Embedded Intelligence on FPGA: Survey, Applications and Challenges
inferredcites →https://doi.org/10.3390/electronics10080952openalex-snapshot
GPU-Based Embedded Intelligence Architectures and Applications
inferredcites →https://doi.org/10.3390/fi10100093openalex-snapshot
Proactive Caching at the Edge Leveraging Influential User Detection in Cellular D2D Networks
inferredcites →https://doi.org/10.48550/arxiv.1211.5063openalex-snapshot
On the difficulty of training Recurrent Neural Networks
inferredcites →https://doi.org/10.5772/intechopen.97197openalex-snapshot
Management of Software-Defined Networking Powered by Artificial Intelligence
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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