STUDY;TITLE;DOI;ISSN;ISBN;URL;YEAR;ALGORITHMS;METRICS;DATASET;ENERGY;MICROCONTROLLER ;COMUNICATION
S1 ; IKW: Inter-Kernel Weights for Power Efficient Edge Computing;10.1109/ACCESS.2020.2993506;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9090142;2020;CNN, VGG, Inception;Accuracy;CIFAR-10;;;
S2 ; Image Classification Model Using Deep Learning on the Edge Device;10.1007/978-981-15-5959-4_2;;;http://link.springer.com/chapter/10.1007/978-981-15-5959-4_2;2020;Inception;ROC, Recall;MNIST;;Raspberry Pi;
S3 ; Image Search System Based on Feature Vectors of Convolutional Neural Network;10.1109/TENCON50793.2020.9293773;2159-3450;978-1-7281-8455-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9293773;2020;CNN, MobileNet;Accuracy;CIFAR-10;;Raspberry Pi;
S4 ; IMPACT: Impersonation Attack Detection via Edge Computing Using Deep Autoencoder and Feature Abstraction;10.1109/ACCESS.2020.2985089;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9055368;2020;SVM;Accuracy, Detection Rate, F-measure, FAR, Mathew’s correlation coefficient, Time To Build (TTB);OTROS;;;
S5 ; Implementation of Fire and Smoke Detection using DeepStream and Edge Computing Approachs;10.1109/ICPAI51961.2020.00058;;978-0-7381-4262-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9302759;2020;YOLO;MAP, Recall;;;Jetson NX Xavier;
S6 ; Intelligent Fault Diagnosis for Large-Scale Rotating Machines Using Binarized Deep Neural Networks and Random Forests;10.1109/TASE.2020.3048056;1558-3783;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9326384;2021;DNN, CNN, SVM, RF;Accuracy, F-measure;OTROS;;;
S7 ; Intelligent sentiment analysis approach using edge computing-based deep learning technique;https://doi.org/10.1002/spe.2687; ;;https://onlinelibrary.wiley.com/doi/abs/10.1002/spe.2687;2020;CNN;Accuracy, F-measure;OTROS;;;
S8 ; Intent-Based Network for Data Dissemination in Software-Defined Vehicular Edge Computing;10.1109/TITS.2020.3002349;1558-0016;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9123601;2020;CNN;;;;;
S9 ; Interpretable Machine Learning In Sustainable Edge Computing: A Case Study of Short-Term Photovoltaic Power Output Prediction;10.1109/ICASSP40776.2020.9054088;2379-190X;978-1-5090-6631-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9054088;2020;LSTM, SVR;MAE, R2, RMSE;OTROS;Solar;;
S10 ; Intrusion detection in Edge-of-Things computing;https://doi.org/10.1016/j.jpdc.2019.12.008;0743-7315;;https://www.sciencedirect.com/science/article/pii/S074373151930872X;2020;ANN, SVM;Accuracy;OTROS;;;
S11 ; IONN: Incremental Offloading of Neural Network Computations from Mobile Devices to Edge Servers;10.1145/3267809.3267828;9.78E+12;;https://doi.org/10.1145/3267809.3267828;2018;AlexNet, MobileNet, Inception, ResNet, GOOGLE NET;;;;;
S12 ; IoT-Enabled Streaming Image Analytics With Privacy-Aware Self-Adaptive and Reflective Designs;10.1109/JSYST.2020.2983057;1937-9234;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9078779;2021;YOLO;Precision;PASCAL;;;
S13 ; iSEC: An Optimized Deep Learning Model for Image Classification on Edge Computing;10.1109/ACCESS.2020.2971566;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8981999;2020;VGG, MobileNet, Inception;Accuracy;CIFAR-10;;Raspberry Pi;
S14 ; iWEP: An Intelligent WLAN Early Warning Platform Using Edge Computing;10.1109/MSN48538.2019.00079;;978-1-7281-5212-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9066146;2019;ANN, LoR;Accuracy;CIFAR-10;;;
S15 ; JALAD: Joint Accuracy-And Latency-Aware Deep Structure Decoupling for Edge-Cloud Execution;10.1109/PADSW.2018.8645013;1521-9097;978-1-5386-7308-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8645013;2018;ANN, VGG;;;;;
S16 ; Knowledge-Driven Service Offloading Decision for Vehicular Edge Computing: A Deep Reinforcement Learning Approach;10.1109/TVT.2019.2894437;1939-9359;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8620546;2019;DRL;;;;;
S17 ; Kriging-Bootstrapped DNN Hierarchical Model for Real-Time Seizure Detection from EEG Signals;10.1109/WF-IoT48130.2020.9221480;;978-1-7281-5503-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9221480;2020;DNN;Accuracy;CIFAR-10;;;
S18 ; Learning Centric Wireless Resource Allocation for Edge Computing: Algorithm and Experiment;10.1109/TVT.2020.3047149;1939-9359;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9307274;2021;CNN, SVM;Accuracy;MNIST, DIGITS;;Raspberry Pi;Wi-Fi
S19 ; Leveraging Memory PUFs and PIM-based encryption to secure edge deep learning systems;10.1109/VTS.2019.8758660;2375-1053;978-1-7281-1170-4;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8758660;2019;LeNet, MLP ;Accuracy;CIFAR-10, MNIST;;;
S20 ; Lightweight Convolution Neural Networks for Mobile Edge Computing in Transportation Cyber Physical Systems;10.1145/3339308;2157-6904;;https://doi.org/10.1145/3339308;2019;AlexNet, VGG;Accuracy;OTROS;Continua;Jetson TX2;Wireless
S21 ; Lightweight Deep Learning Based Intelligent Edge Surveillance Techniques;10.1109/TCCN.2020.2999479;2332-7731;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9106357;2020;MobileNet, YOLO;MAP;;;Jetson TX2;
S22 ; Lightweight Deep Learning Model in Mobile Edge Computing for Radar-Based Human Activity Recognition;10.1109/JIOT.2021.3063504;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9367279;2021;CNN, MLP , ResNet;Accuracy;CIFAR-10;;Otro;
S23 ; Low power AI hardware platform for deep learning in edge computing;10.1109/ICSJ.2018.8602619;2475-8418;978-1-5386-5442-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8602619;2018;VGG, ResNet, GOOGLE NET;;;USB;;
S24 ; Low-Latency Energy-Efficient Cyber-Physical Disaster System Using Edge Deep Learning;10.1145/3369740.3372752;9.78E+12;;https://doi.org/10.1145/3369740.3372752;2020;VGG, MobileNet, Inception;Accuracy, F-measure, Precision, Recall;CIFAR-10, PASCAL;;Raspberry Pi;Bluetooth
S25 ; Low-Latency Privacy-Preserving Outsourcing of Deep Neural Network Inference;10.1109/JIOT.2020.3003468;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9120239;2021;AlexNet;;;USB;Raspberry Pi;
S26 ; Low-Power HWAccelerator for AI Edge-Computing in Human Activity Recognition Systems;10.1109/AICAS48895.2020.9073913;;978-1-7281-4922-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9073913;2020;;Accuracy;CIFAR-10;;;
S27 ; LRA-3C: Learning Based Resource Allocation for Communication-Computing-Caching Systems;10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00150;;978-1-7281-2980-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8875292;2019;ANN;Accuracy;CIFAR-10;;;
S28 ; Lucid: A Practical, Lightweight Deep Learning Solution for DDoS Attack Detection;10.1109/TNSM.2020.2971776;1932-4537;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8984222;2020;CNN, LSTM, MLP ;Accuracy, F-measure, Otro;OTROS;;Raspberry Pi, Jetson TX2;
S29 ; Machine Learning Agricultural Application Based on the Secure Edge Computing Platform;10.1007/978-3-030-62223-7_18;;;http://link.springer.com/chapter/10.1007/978-3-030-62223-7_18;2020;YOLO;MAP;FRUIT;;Jetson TX2;
S30 ; Machine Learning Assisted Content Delivery at Edge of Mobile Social Networks;10.1109/DSC.2019.00075;;978-1-7281-4528-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8923784;2019;ANN, SVM, RF, LiR;MAE, RMSE;;;;
S31 ; Machine Learning Based Transformer Health Monitoring Using IoT Edge Computing;10.1109/ICCCS49678.2020.9276889;;978-1-7281-9180-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9276889;2020;RF, KNN, NB;Accuracy, Sensitivity, Specificity;CIFAR-10;;Jetson Nano ;
S32 ; Machine learning versus ray-tracing to forecast irradiance for an edge-computing SkyImager;10.1109/ISAP.2017.8071425;;978-1-5090-4000-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8071425;2017;MLP ;Accuracy;OTROS;;Raspberry Pi;
S33 ; Machine learning-based edge-computing on a multi-level architecture of WSN and IoT for real-time fall detection;https://doi.org/10.1049/iet-wss.2020.0091; ;;https://onlinelibrary.wiley.com/doi/abs/10.1049/iet-wss.2020.0091;2020;ANN, SVM, RF, KNN;Accuracy;OTROS;Batería;Raspberry Pi;
S34 ; Machine Learning-Based Task Clustering for Enhanced Virtual Machine Utilization in Edge Computing;10.1109/CCECE47787.2020.9255811;2576-7046;978-1-7281-5442-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9255811;2020;K-means;;;;;
S35 ; Machine Learning-Driven Scaling and Placement of Virtual Network Functions at the Network Edges;10.1109/NETSOFT.2019.8806631;;978-1-5386-9376-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8806631;2019;MLP , SVM, DT, KNN, NB;Accuracy, F-measure, Precision, Recall;CIFAR-10, PASCAL;;;
S36 ; Machine Learning-Driven Trust Prediction for MEC-Based IoT Services;10.1109/ICWS.2019.00040;;978-1-7281-2717-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8818406;2019;SVM;Accuracy;OTROS;;;
S37 ; MBBNet: An edge IoT computing-based traffic light detection solution for autonomous bus;https://doi.org/10.1016/j.sysarc.2020.101835;1383-7621;;https://www.sciencedirect.com/science/article/pii/S1383762120301272;2020;CNN, VGG, ResNet;F-measure, MAP, Precision, Recall, Otro;IMAGENET, COCO;;;
S38 ; MeFILL: A Multi-edged Framework for Intelligent and Low Latency Mobile IoT Services;10.1109/WCNC45663.2020.9120786;1558-2612;978-1-7281-3106-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9120786;2020;MobileNet, YOLO, FL;Latency, MAP;COCO;Continua;Raspberry Pi;
S39 ; Memristor Based Variation Enabled Differentially Private Learning Systems for Edge Computing in IoT;10.1109/JIOT.2020.3023623;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9194756;2020;MLP ;;MNIST;;;
S40 ; Memristor-based Edge Computing of ShuffleNetV2 for Image Classification;10.1109/TCAD.2020.3022970;1937-4151;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9193925;2020;;;OTROS;;;
S41 ; Meta-Learning based Dynamic Computation Task Offloading for Mobile Edge Computing Networks;10.1109/LCOMM.2020.3048075;1558-2558;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9310298;2020;DNN;;;;;
S42 ; Method for detection of unsafe actions in power field based on edge computing architecture;10.1186/s13677-021-00234-w;;;http://link.springer.com/article/10.1186/s13677-021-00234-w;2021;RNN, GRU, YOLO;Accuracy;CIFAR-10;;Raspberry Pi;Wi-Fi
S43 ; Migrating Intelligence from Cloud to Ultra-Edge Smart IoT Sensor Based on Deep Learning: An Arrhythmia Monitoring Use-Case;10.1109/IWCMC48107.2020.9148134;2376-6506;978-1-7281-3129-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9148134;2020;CNN, SVM, RF;Accuracy, F-measure, Precision;OTROS;;Raspberry Pi, Jetson Nano ;
S44 ; Millimetre Wave Receiver of Radar Detection with Deep Learning for ADAS Edge Computing Vision;10.1109/IMPACT50485.2020.9268553;2150-5942;978-1-7281-9851-4;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9268553;2020;MobileNet;;;;;
S45 ; ML-Driven DASH Content Pre-Fetching in MEC-Enabled Mobile Networks;10.23919/CNSM50824.2020.9269054;2165-963X;978-3-903176-31-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9269054;2020;RF, GBT;Accuracy;CIFAR-10;;;
S46 ; Mobile Edge Assisted Literal Multi-Dimensional Anomaly Detection of In-Vehicle Network Using LSTM;10.1109/TVT.2019.2907269;1939-9359;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8673868;2019;LeNet, SVM;;;;;
S47 ; Mobile Edge Computing Offloading Strategy Based on Improved BP Neural Network;10.1109/ICCCBDA49378.2020.9095726;;978-1-7281-6024-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9095726;2020;;ROC;MNIST;;;4G/5G
S48 ; Mobile Edge Computing-Based Data-Driven Deep Learning Framework for Anomaly Detection;10.1109/ACCESS.2019.2942485;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8844663;2019;DNN;;;;;
S49 ; Motion Prediction and Pre-Rendering at the Edge to Enable Ultra-Low Latency Mobile 6DoF Experiences;10.1109/OJCOMS.2020.3032608;2644-125X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9234536;2020;LSTM, MLP ;MAE, RMSE;;;;
S50 ; Multiattack Intrusion Detection Algorithm for Edge-Assisted Internet of Things;10.1109/ICII.2019.00046;;978-1-7281-2977-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9065131;2019;RBF, SVM, NB;Accuracy, Undetected Rate;OTROS;;;
S51 ; Multilevel Neural Network for Reducing Expected Inference Time;10.1109/ACCESS.2019.2952577;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8895793;2019;ResNet;ROC;CIFAR-10, IMAGENET;;Otro;
S52 ; Multimodal data analysis of epileptic EEG and rs-fMRI via deep learning and edge computing;https://doi.org/10.1016/j.artmed.2020.101813;0933-3657;;https://www.sciencedirect.com/science/article/pii/S0933365718306882;2020;CNN;Accuracy, False Negative Rate, False Positive Rate, Precision, Sensitivity;OTROS;;;Wireless
S53 ; Multimodal Data Processing Framework for Smart City: A Positional-Attention Based Deep Learning Approach;10.1109/ACCESS.2020.3041447;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9274421;2020;LSTM;;COCO;;;
S54 ; Multispectral Information Fusion With Reinforcement Learning for Object Tracking in IoT Edge Devices;10.1109/JSEN.2019.2962834;1558-1748;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8945145;2020;MobileNet, ResNet, QL ES RL;MAP, MOTA, T racks;OTROS;;;
S55 ; Multistage and Elastic Spam Detection in Mobile Social Networks through Deep Learning;10.1109/MNET.2018.1700406;1558-156X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8425295;2018;CNN, RF, GBT, LoR, NB;Accuracy, F-measure, Precision, Recall;OTROS;;;
S56 ; Multitasks Scheduling in Delay-Bounded Mobile Edge Computing;10.1007/978-3-030-22971-9_19;;;http://link.springer.com/chapter/10.1007/978-3-030-22971-9_19;2019;DQN;;;;;
S57 ; Multi-user Computation Offloading for Mobile Edge Computing: A Deep Reinforcement Learning and Game Theory Approach;10.1109/ICCT50939.2020.9295872;2576-7828;978-1-7281-8141-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9295872;2020;DQN, QL ES RL;;;;;
S58 ; MyDigitalFootprint: An extensive context dataset for pervasive computing applications at the edge;https://doi.org/10.1016/j.pmcj.2020.101309;1574-1192;;https://www.sciencedirect.com/science/article/pii/S1574119220301383;2021;ANN, DT;Accuracy;CIFAR-10;;;
S59 ; NOMA-based energy-efficient task scheduling in vehicular edge computing networks: A self-imitation learning-based approach;10.23919/JCC.2020.11.001;1673-5447;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9267792;2020;DQN;;;;;Wireless
S60 ; Non-Intrusive Appliance Load Monitoring in an Intelligent Device at the Edge layer;10.1109/IJCNN48605.2020.9207155;2161-4407;978-1-7281-6926-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9207155;2020;;Otro;;Continua;Arduino;Wi-Fi
S61 ; Nonlinearity Compensation in A Multi-DoF Shoulder Sensing Exosuit For Real-Time Teleoperation;10.1109/RoboSoft48309.2020.9116031;;978-1-7281-6570-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9116031;2020;ANN, LSTM;RMSE;;;Arduino, Jetson Nano ;
S62 ; Offboard Machine Learning Through Edge Computing for Robotic Applications;10.1109/SECON.2018.8479091;1558-058X;978-1-5386-6133-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8479091;2018;YOLO;;;;;Wi-Fi
S63 ; Offloading Optimization in Edge Computing for Deep Learning Enabled Target Tracking by Internet-of-UAVs;10.1109/JIOT.2020.3016694;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9167249;2020;CNN;;IMAGENET;;Jetson TX2;
S64 ; On Differential Privacy-Based Framework for Enhancing User Data Privacy in Mobile Edge Computing Environment;10.1109/ACCESS.2021.3063603;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9367146;2021;RL;Accuracy;OTROS;;;
S65 ; On non-intrusive prediction of activities and behavior;10.1109/BigData47090.2019.9006126;;978-1-7281-0858-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9006126;2019;SVM, NB;Cross Validation;OTROS;;;
S66 ; On Physical-Layer Authentication via Triple Pool Convolutional Neural Network;10.1109/GCWkshps50303.2020.9367391;;978-1-7281-7307-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9367391;2020;CNN, VGG;;OTROS;;;
S67 ; Online Computation Offloading in NOMA-Based Multi-Access Edge Computing: A Deep Reinforcement Learning Approach;10.1109/ACCESS.2020.2997925;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9102308;2020;DRL;;;;;4G/5G
S68 ; Online Learning and Optimization for Computation Offloading in D2D Edge Computing and Networks;10.1007/s11036-018-1176-y;;;http://link.springer.com/article/10.1007/s11036-018-1176-y;2019;QL ES RL;;;;;Wireless
S69 ; Online Learning for Offloading and Autoscaling in Energy Harvesting Mobile Edge Computing;10.1109/TCCN.2017.2725277;2332-7731;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7973020;2017;QL ES RL;;;Solar;;
S70 ; Online Proactive Caching in Mobile Edge Computing Using Bidirectional Deep Recurrent Neural Network;10.1109/JIOT.2019.2903245;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8660445;2019;;;;;;
S71 ; Optimization of Deep Learning Inference on Edge Devices;10.1109/ICPAI51961.2020.00056;;978-0-7381-4262-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9302695;2020;MobileNet, Inception;Accuracy;CIFAR-10;;Raspberry Pi;
S72 ; P3M: A PIM-Based Neural Network Model Protection Scheme for Deep Learning Accelerator;10.1145/3287624.3287695;9.78E+12;;https://doi.org/10.1145/3287624.3287695;2019;LeNet, MLP , ResNet, GOOGLE NET;Accuracy;CIFAR-10, MNIST, IMAGENET;;;
S73 ; PerDNN: Offloading Deep Neural Network Computations to Pervasive Edge Servers;10.1109/ICDCS47774.2020.00114;2575-8411;978-1-7281-7002-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9355588;2020;RNN, MobileNet, Inception, ResNet;Errors;OTROS;;;
S74 ; Performance analysis of local exit for distributed deep neural networks over cloud and edge computing;https://doi.org/10.4218/etrij.2020-0112; ;;https://onlinelibrary.wiley.com/doi/abs/10.4218/etrij.2020-0112;2020;CNN;Accuracy;CIFAR-10;;Raspberry Pi;
S75 ; Performance Evaluation of Edge Computing-Based Deep Learning Object Detection;10.1145/3301326.3301369;9.78E+12;;https://doi.org/10.1145/3301326.3301369;2018;MobileNet;MAP;PASCAL;;Raspberry Pi;Bluetooth, Wi-Fi
S76 ; Performance evaluation of edge-computing platforms for the prediction of low temperatures in agriculture using deep learning;10.1007/s11227-020-03288-w;;;http://link.springer.com/article/10.1007/s11227-020-03288-w;2021;LSTM;MAE, RMSE, Otro;;Batería;Jetson NX Xavier;Otro
S77 ; Porting Rulex Machine Learning Software to the Raspberry Pi as an Edge Computing Device;10.1007/978-3-030-66729-0_33;;;http://link.springer.com/chapter/10.1007/978-3-030-66729-0_33;2021;;ROC;MNIST;;Raspberry Pi;Wi-Fi
S78 ; Poster: Lambda architecture for robust condition based maintenance with simulated failure modes;10.1109/SEC50012.2020.00019;;978-1-7281-5943-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9355694;2020;CNN;Accuracy;CIFAR-10;;Raspberry Pi;
S79 ; Pothole Detection and Avoidance via Deep Learning on Edge Devices;10.1109/CACS50047.2020.9289701;;978-1-7281-7198-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9289701;2020;DQN;ROC;MNIST;;;
S80 ; Predicted Mobile Data Offloading for Mobile Edge Computing Systems;10.1007/978-3-030-05755-8_16;;;http://link.springer.com/chapter/10.1007/978-3-030-05755-8_16;2018;LSTM;Otro;OTROS;;;Wi-Fi
S81 ; Prediction of thermal energy inside smart homes using IoT and classifier ensemble techniques;https://doi.org/10.1016/j.comcom.2019.12.020;0140-3664;;https://www.sciencedirect.com/science/article/pii/S0140366419313416;2020;CNN, SVM, RF;Accuracy, Cross Validation, R2, Otro;CIFAR-10, OTROS;;;
S82 ; Predictive GPU-based ADAS Management in Energy-Conscious Smart Cities;10.1109/ISC246665.2019.9071685;2687-8860;978-1-7281-0846-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9071685;2019;LSTM, GRU;R2, Otro;CIFAR-10;;;
S83 ; Predictive Online Server Provisioning for Cost-Efficient IoT Data Streaming Across Collaborative Edges;10.1145/3323679.3326530;9.78E+12;;https://doi.org/10.1145/3323679.3326530;2019;LSTM;;;;;
S84 ; PriSE: Slenderized Privacy-Preserving Surveillance as an Edge Service;10.1109/CIC50333.2020.00024;;978-1-7281-4146-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9319016;2020;FACENET, SVM;;OTROS;;Raspberry Pi;Bluetooth
S85 ; Privacy is What We Care About: Experimental Investigation of Federated Learning on Edge Devices;10.1145/3363347.3363365;9.78E+12;;https://doi.org/10.1145/3363347.3363365;2019;CNN, LSTM, MLP ;;CIFAR-10, MNIST;;Raspberry Pi;
S86 ; Privacy-Enhanced Data Collection Based on Deep Learning for Internet of Vehicles;10.1109/TII.2019.2962844;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8945334;2020;CNN;Accuracy, ROC;CIFAR-10, MNIST;;;4G/5G
S87 ; Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices;10.1109/JIOT.2020.3017377;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9170559;2021;CNN, FL;Accuracy;MNIST;;Raspberry Pi;
S88 ; Privacy-Preserving Compressive Model for Enhanced Deep-Learning-Based Service Provision System in Edge Computing;10.1109/ACCESS.2019.2927163;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8756187;2019;CNN;;CIFAR-10, MNIST;;;
S89 ; Privacy-Preserving Machine Learning Based Data Analytics on Edge Devices;10.1145/3278721.3278778;9.78E+12;;https://doi.org/10.1145/3278721.3278778;2018;LeNet, VGG, Inception;;;;;
S90 ; Proactive Video Push for Optimizing Bandwidth Consumption in Hybrid CDN-P2P VoD Systems;10.1109/INFOCOM.2018.8485962;;978-1-5386-4128-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8485962;2018;LSTM, SVM, DT;ROC;MNIST;;;
S91 ; Prototype Development of Face and Speaker Recognitions based on Edge Computing;10.1109/ISNCC49221.2020.9297243;;978-1-7281-5628-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9297243;2020;FACENET;Accuracy;OTROS;;;
S92 ; QoE-driven big data management in pervasive edge computing environment;10.26599/BDMA.2018.9020020;2096-0654;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8361574;2018;FCN/FRCNN;Accuracy, Precision, Recall;OTROS;;;
S93 ; QoS Evaluation and Prediction for C-V2X Communication in Commercially-Deployed LTE and Mobile Edge Networks;10.1109/VTC2020-Spring48590.2020.9129382;2577-2465;978-1-7281-5207-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9129382;2020;ANN, RNN, SVM, RT;Accuracy;CIFAR-10;;;
S94 ; QoS-enabled resource allocation algorithm in internet of vehicles with mobile edge computing;https://doi.org/10.1049/iet-com.2019.0981; ;;https://onlinelibrary.wiley.com/doi/abs/10.1049/iet-com.2019.0981;2020;QL ES RL;;;;;4G/5G
S95 ; Quality of Service Channelling for Latency Sensitive Edge Applications;10.1109/IEEE.EDGE.2017.30;;978-1-5386-2017-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8029271;2017;LoR, NB;Accuracy;OTROS;;;
S96 ; Quality of Service Optimization in Mobile Edge Computing Networks via Deep Reinforcement Learning;10.1007/978-3-030-59016-1_13;;;http://link.springer.com/chapter/10.1007/978-3-030-59016-1_13;2020;DQN, QL ES RL;;;;;
S97 ; Quantitative Analysis of Deep Leaf: a Plant Disease Detector on the Smart Edge;10.1109/SMARTCOMP50058.2020.00027;;978-1-7281-6997-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9239642;2020;CNN;F-measure, Precision, Recall, Otro;PASCAL;;Otro;
S98 ; Quantized Convolutional Neural Network toward Real-time Arrhythmia Detection in Edge Device;10.1109/ICRAMET51080.2020.9298667;;978-1-7281-8922-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9298667;2020;CNN, LSTM, SVM;;OTROS;;Raspberry Pi, Jetson Nano , Otro;
S99 ; Real Time Baby Facial Expression Recognition Using Deep Learning and IoT Edge Computing;10.1109/ICCCS49678.2020.9277428;;978-1-7281-9180-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9277428;2020;CNN, SVM, KNN;F-measure, Precision, Recall;OTROS;;Jetson Nano ;
S100 ; Realising Edge Analytics for Early Prediction of Readmission: A Case Study;10.1109/IC2E48712.2020.00017;;978-1-7281-1099-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9096429;2020;ELM;Accuracy, F-measure, Precision, Recall;CIFAR-10, PASCAL;;;
S101 ; Real-Time CPU Scheduling Approach for Mobile Edge Computing System;10.1007/978-3-319-94965-9_4;;;http://link.springer.com/chapter/10.1007/978-3-319-94965-9_4;2018;SVM;Accuracy, Loss Rate;CIFAR-10;;;4G/5G
S102 ; Real-time Crop Classification Using Edge Computing and Deep Learning;10.1109/CCNC46108.2020.9045498;2331-9860;978-1-7281-3893-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9045498;2020;AlexNet, CNN, SegNet;Recall;;;;Wireless
S103 ; Real-Time Fault Detection for IIoT Facilities Using GBRBM-Based DNN;10.1109/JIOT.2019.2948396;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8877731;2020;SVM, RL;Accuracy;CIFAR-10;;;
S104 ; Real-Time Human Detection as an Edge Service Enabled by a Lightweight CNN;10.1109/EDGE.2018.00025;;978-1-5386-7238-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8473387;2018;CNN, MobileNet, GOOGLE NET, SVM;False Negative Rate, False Positive Rate;OTROS;;Raspberry Pi;
S105 ; Real-time Mask Identification for COVID-19: An Edge Computing-based Deep Learning Framework;10.1109/JIOT.2021.3051844;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9324817;2021;CNN, FACENET;Accuracy;OTROS;;Raspberry Pi;
S106 ; Real-Time Radar-Based Gesture Detection and Recognition Built in an Edge-Computing Platform;10.1109/JSEN.2020.2994292;1558-1748;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9092991;2020;;Accuracy, F-measure;CIFAR-10, PASCAL;;Jetson Nano ;
S107 ; Real-time Situation Awareness of Industrial Process based on Deep Learning at the Edge Server;10.1109/CCGrid49817.2020.000-3;;978-1-7281-6095-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9139691;2020;;Accuracy;CIFAR-10;;;
S108 ; Reinforcement Learning-Based Computing and Transmission Scheduling for LTE-U-Enabled IoT;10.1109/GLOCOM.2018.8647178;2576-6813;978-1-5386-4727-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8647178;2018;DQL;;;;;Wi-Fi
S109 ; Remaining useful life prediction based on state assessment using edge computing on deep learning;https://doi.org/10.1016/j.comcom.2020.05.035;0140-3664;;https://www.sciencedirect.com/science/article/pii/S0140366420306277;2020;DNN, CNN, ANN, LSTM, RNN, GRU;;OTROS;;Raspberry Pi;
S110 ; Reputation-based Miner Node Selection in Blockchain-based Vehicular Edge Computing;10.1109/MCE.2020.3048312;2162-2256;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9311777;2020;ANN;;;;;
S111 ; RES: Real-time Video Stream Analytics using Edge Enhanced Clouds;10.1109/TCC.2020.2991748;2168-7161;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9084281;2020;MobileNet;Accuracy;OTROS;;;
S112 ; Research on Aided Reading System of Digital Library Based on Text Image Features and Edge Computing;10.1109/ACCESS.2020.3037349;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9256280;2020;;ROC;MNIST;;;
S113 ; Research on Big Data Processing Model of Edge-Cloud Collaboration in Cyber Physical Systems;10.1109/ICBDA49040.2020.9101197;;978-1-7281-4111-4;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9101197;2020;ANN;Otro;;;;
S114 ; Research on Traffic Accident Prediction Model Based on Convolutional Neural Networks in VANET;10.1109/ICAIBD.2019.8837020;;978-1-7281-0831-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8837020;2019;CNN;Accuracy;OTROS;;;
S115 ; Resource Offload Consolidation Based on Deep-Reinforcement Learning Approach in Cyber-Physical Systems;10.1109/TETCI.2020.3044082;2471-285X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9309331;2020;QL ES RL;;;;;
S116 ; RILOD: Near Real-Time Incremental Learning for Object Detection at the Edge;10.1145/3318216.3363317;9.78E+12;;https://doi.org/10.1145/3318216.3363317;2019;ResNet;MAP;COCO, PASCAL;;;
S117 ; Robustness analytics to data heterogeneity in edge computing;https://doi.org/10.1016/j.comcom.2020.10.020;0140-3664;;https://www.sciencedirect.com/science/article/pii/S014036642031968X;2020;FL;Accuracy;CIFAR-10;;;
S118 ; RoPE: An Architecture for Adaptive Data-Driven Routing Prediction at the Edge;10.1109/TNSM.2020.2980899;1932-4537;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9037103;2020;SVM, RT, LiR;MAPE, MAXE, RMSE;;;;
S119 ; Scheduling-Efficient Framework for Neural Network on Heterogeneous Distributed Systems and Mobile Edge Computing Systems;10.1109/ACCESS.2019.2954897;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8908789;2019;LeNet, DENSENET, ResNet;Accuracy;CIFAR-10;;;
S120 ; Scission: Performance-driven and Context-aware Cloud-Edge Distribution of Deep Neural Networks;10.1109/UCC48980.2020.00044;;978-0-7381-2394-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9302776;2020;DENSENET, VGG, MobileNet, Inception, ResNet;;;;;
S121 ; SDN-Based Multi-Tier Computing and Communication Architecture for Pervasive Healthcare;10.1109/ACCESS.2018.2873907;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8482108;2018;SVM, RF;Accuracy, ROC;CIFAR-10, MNIST;;;
S122 ; Secure and Verifiable Multi-key Image Search in Cloud-Assisted Edge Computing;10.1109/TII.2020.3032147;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9229509;2020;CNN, KNN;;;;;
S123 ; Secure Blockchain-Based Traffic Load Balancing Using Edge Computing and Reinforcement Learning;10.1007/978-3-030-38181-3_6;;;http://link.springer.com/chapter/10.1007/978-3-030-38181-3_6;2020;RL;;;;Raspberry Pi;
S124 ; Secure Real-Time Heterogeneous IoT Data Management System;10.1109/TPS-ISA48467.2019.00037;;978-1-7281-6741-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9014355;2019;YOLO;Accuracy;OTROS;;;
S125 ; SecureAD: A Secure Video Anomaly Detection Framework on Convolutional Neural Network in Edge Computing Environment;10.1109/TCC.2020.2990946;2168-7161;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9079678;2020;LSTM;False Positive Rate;OTROS;;;
S126 ; Securing Deep Learning Based Edge Finger Vein Biometrics With Binary Decision Diagram;10.1109/TII.2019.2900665;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8648285;2019;CNN;;OTROS;;;
S127 ; Security Enhancement for Mobile Edge Computing Through Physical Layer Authentication;10.1109/ACCESS.2019.2934122;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8793124;2019;CNN;Otro;;;;
S128 ; Self-Driving Car Meets Multi-Access Edge Computing for Deep Learning-Based Caching;10.1109/ICOIN.2019.8718113;1976-7684;978-1-5386-8350-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8718113;2019;CNN, MLP ;Otro;OTROS;;;Wi-Fi
S129 ; Semi-Skipping Layered Gated Unit and Efficient Network: Hybrid Deep Feature Selection Method for Edge Computing in EEG-Based Emotion Classification;10.1109/ACCESS.2021.3051808;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9323045;2021;GRU, SVM, KNN, NB;Accuracy, F-measure, Precision, Recall;OTROS;;;
S130 ; Semisupervised Distributed Learning With Non-IID Data for AIoT Service Platform;10.1109/JIOT.2020.2995162;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9094657;2020;CNN, FL;Accuracy;CIFAR-10;;;
S131 ; Short-Term Traffic Prediction for Edge Computing-Enhanced Autonomous and Connected Cars;10.1109/TVT.2019.2899125;1939-9359;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8641378;2019;LSTM;;;;;
S132 ; Shredder: Learning Noise Distributions to Protect Inference Privacy;10.1145/3373376.3378522;9.78E+12;;https://doi.org/10.1145/3373376.3378522;2020;AlexNet, LeNet, VGG;Loss Rate, Otro;OTROS;;;
S133 ; Siamese Networks for Few-Shot Learning on Edge Embedded Devices;10.1109/JETCAS.2020.3033155;2156-3365;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9235455;2020;CNN;;CIFAR-10, MNIST, IMAGENET;;;
S134 ; Simplicity is Best: Addressing the Computational Cost of Machine Learning Classifiers in Constrained Edge Devices;10.1145/3365871.3365889;9.78E+12;;https://doi.org/10.1145/3365871.3365889;2019;MLP , SVM, DT, RF, LoR, KNN, NB;Accuracy, F-measure, Precision, Recall;OTROS;;Raspberry Pi;
S135 ; SleepGuardian: An RF-Based Healthcare System Guarding Your Sleep from Afar;10.1109/MNET.001.1900235;1558-156X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9003372;2020;KNN;Accuracy;CIFAR-10;;;Wi-Fi
S136 ; Smart Classrooms Aided by Deep Neural Networks Inference on Mobile Devices;10.1109/EIT.2018.8500260;2154-0373;978-1-5386-5398-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8500260;2018;MobileNet, Inception;;;;Raspberry Pi;Bluetooth
S137 ; Smart electronic gastroscope system using a cloud–edge collaborative framework;https://doi.org/10.1016/j.future.2019.04.031;0167-739X;;https://www.sciencedirect.com/science/article/pii/S0167739X18324324;2019;YOLO;;;;;
S138 ; Smart Health Monitoring for Seizure Detection using Mobile Edge Computing;10.1109/IWCMC48107.2020.9148418;2376-6506;978-1-7281-3129-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9148418;2020;CNN;Accuracy, F-measure;OTROS;;Raspberry Pi;Wireless
S139 ; Smart Healthcare Analysis and Therapy for Voice Disorder using Cloud and Edge Computing;10.1109/iCATccT44854.2018.9001280;;978-1-5386-7706-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9001280;2018;CNN;;;;;Wi-Fi
S140 ; Smart Healthy Intelligent Room: Headcount through Air Quality Monitoring;10.1109/SMARTCOMP50058.2020.00071;;978-1-7281-6997-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9239659;2020;MLP , SVM, RF, KNN;;;;;
S141 ; Smart Illegal Dumping Detection;10.1109/BigDataService.2017.51;;978-1-5090-6318-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7944947;2017;AlexNet, GOOGLE NET;Accuracy;IMAGENET;;;
S142 ; Smart Manufacturing Scheduling With Edge Computing Using Multiclass Deep Q Network;10.1109/TII.2019.2908210;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8676376;2019;DQN;;;;;
S143 ; Smart Parking with Fine-Grained Localization and User Status Sensing Based on Edge Computing;10.1109/VTCFall.2019.8891560;2577-2465;978-1-7281-1220-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8891560;2019;CNN, MLP , SVM;Accuracy;CIFAR-10;;;
S144 ; Smart Surveillance as an Edge Network Service: From Harr-Cascade, SVM to a Lightweight CNN;10.1109/CIC.2018.00042;;978-1-5386-9502-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8537840;2018;CNN, MobileNet, GOOGLE NET, SVM;False Negative Rate, False Positive Rate;OTROS;;Raspberry Pi;
S145 ; Smart water conservation through a machine learning and blockchain-enabled decentralized edge computing network;https://doi.org/10.1016/j.asoc.2021.107274;1568-4946;;https://www.sciencedirect.com/science/article/pii/S1568494621001976;2021;FFNN;Otro;;;;
S146 ; Smart, Secure, Yet Energy-Efficient, Internet-of-Things Sensors;10.1109/TMSCS.2018.2864297;2332-7766;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8432098;2018;SVM, K-means;Accuracy;OTROS;;;
S147 ; SO-VMEC: Service offloading in virtual mobile edge computing using deep reinforcement learning;https://doi.org/10.1002/ett.4211; ;;https://onlinelibrary.wiley.com/doi/abs/10.1002/ett.4211;2021;LSTM, DRL, GRU;;;;;
S148 ; Spectrum Awareness at the Edge: Modulation Classification using Smartphones;10.1109/DySPAN.2019.8935775;2334-3125;978-1-7281-2376-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8935775;2019;CNN;Accuracy;OTROS;;;Wireless
S149 ; Squeezed Convolutional Variational AutoEncoder for unsupervised anomaly detection in edge device industrial Internet of Things;10.1109/INFOCT.2018.8356842;;978-1-5386-5384-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8356842;2018;SVM;ROC, Precision, Recall;OTROS;;;
S150 ; Stacked Autoencoder-Based Deep Reinforcement Learning for Online Resource Scheduling in Large-Scale MEC Networks;10.1109/JIOT.2020.2988457;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9070170;2020;DRL;Accuracy;CIFAR-10;;;
S151 ; State of Energy Prediction in Renewable Energy-driven Mobile Edge Computing using CNN-LSTM Networks;10.1109/IGESSC50231.2020.9285102;2640-0138;978-1-7281-8744-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9285102;2020;LSTM, RNN;MAE, RMSE;;Solar, Batería;Raspberry Pi;
S152 ; Steward: Smart Edge Based Joint QoE Optimization for Adaptive Video Streaming;10.1145/3304112.3325603;9.78E+12;;https://doi.org/10.1145/3304112.3325603;2019;DRL;Otro;OTROS;;;
S153 ; Strategies for Re-Training a Pruned Neural Network in an Edge Computing Paradigm;10.1109/IEEE.EDGE.2017.45;;978-1-5386-2017-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8029286;2017;MLP ;;;;;Wireless
S154 ; Stress-Lysis: A DNN-Integrated Edge Device for Stress Level Detection in the IoMT;10.1109/TCE.2019.2940472;1558-4127;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8830476;2019;DNN;Accuracy, Precision, Recall;CIFAR-10;;Raspberry Pi;
S155 ; Support vector machine and YOLO for a mobile food grading system;https://doi.org/10.1016/j.iot.2021.100359;2542-6605;;https://www.sciencedirect.com/science/article/pii/S2542660521000032;2021;YOLO, SVM, RF, KNN, NB;;;;;
S156 ; Supporting Delay-Sensitive IoT Applications: A Machine Learning Approach;10.1109/CCECE47787.2020.9255800;2576-7046;978-1-7281-5442-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9255800;2020;DT;Accuracy, Precision, Recall;CIFAR-10;;;
S157 ; Sustainable Deep Learning at Grid Edge for Real-time High Impedance Fault Detection;10.1109/TSUSC.2018.2879960;2377-3782;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8526333;2018;CNN, ANN, SVM;Accuracy, Sensitivity;CIFAR-10;;Otro;Wireless
S158 ; Sustainable Vehicle-Assisted Edge Computing for Big Data Migration in Smart Cities;10.1109/JIOT.2019.2957127;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8920089;2020;MLP ;Accuracy;CIFAR-10;;;
S159 ; Task Classification and Scheduling Based on K-Means Clustering for Edge Computing;10.1007/s11277-020-07343-w;;;http://link.springer.com/article/10.1007/s11277-020-07343-w;2020;K-means;;;;;
S160 ; Task Merging and Scheduling for Parallel Deep Learning Applications in Mobile Edge Computing;10.1109/PDCAT46702.2019.00022;2640-6721;978-1-7281-2616-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9029054;2019;VGG, ResNet;;;;Raspberry Pi;
S161 ; Task Migration Using Q-Learning Network Selection for Edge Computing in Heterogeneous Wireless Networks;10.1007/978-3-030-44751-9_13;;;http://link.springer.com/chapter/10.1007/978-3-030-44751-9_13;2020;DQL, YOLO;;;;;Wireless, 4G/5G, Wi-Fi, Otro
S162 ; TeamNet: A Collaborative Inference Framework on the Edge;10.1109/ICDCS.2019.00148;2575-8411;978-1-7281-2519-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8885231;2019;CNN, MLP ;Accuracy;CIFAR-10, MNIST;;Raspberry Pi, Jetson TX2, Otro;Wi-Fi
S163 ; Temporal difference based adaptive object Detection (ToDo) platform at Edge Computing System;10.1109/CCNC46108.2020.9045513;2331-9860;978-1-7281-3893-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9045513;2020;YOLO;Accuracy;CIFAR-10;;;
S164 ; The analysis of intelligent real-time image recognition technology based on mobile edge computing and deep learning;10.1007/s11554-020-01039-x;;;http://link.springer.com/article/10.1007/s11554-020-01039-x;2020;CNN;Accuracy, MAP, Recall;OTROS;;;
S165 ; The Design of a Novel Smart Home Control System using Smart Grid Based on Edge and Cloud Computing;10.1109/SEGE49949.2020.9181961;2575-2693;978-1-7281-9912-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9181961;2020;DT;;;;Raspberry Pi;Wireless
S166 ; The Recombination of Gesture Nodes Enables Higher Accuracy in Small Data Sets;10.1109/NICOInt.2019.00022;;978-1-7281-4021-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8949306;2019;BPNN;Accuracy;CIFAR-10;;Raspberry Pi;
S167 ; TiFL: A Tier-Based Federated Learning System;10.1145/3369583.3392686;9.78E+12;;https://doi.org/10.1145/3369583.3392686;2020;CNN, FL;Accuracy;CIFAR-10, MNIST;;;
S168 ; Tiny Neural Networks for Environmental Predictions: An Integrated Approach with Miosix;10.1109/SMARTCOMP50058.2020.00076;;978-1-7281-6997-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9239623;2020;LSTM, GRU;MAE, RMSE;;USB;Raspberry Pi;
S169 ; Tool Remaining Useful Life Prediction based on Edge Data Processing and LSTM Recurrent Neural Network;10.1109/ICPHM49022.2020.9187037;;978-1-7281-6286-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9187037;2020;ANN, LSTM;MAE;;;;
S170 ; Toward Communication-Efficient Federated Learning in the Internet of Things With Edge Computing;10.1109/JIOT.2020.2994596;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9094218;2020;AlexNet, LeNet, DENSENET, FL;Accuracy;CIFAR-10, MNIST, IMAGENET;;;
S171 ; Toward Data-Adaptable TinyML Using Model Partial Replacement for Resource Frugal Edge Device;10.1145/3432261.3439865;9.78E+12;;https://doi.org/10.1145/3432261.3439865;2021;;Accuracy;OTROS;;;
S172 ; Toward Direct Edge-to-Edge Transfer Learning for IoT-Enabled Edge Cameras;10.1109/JIOT.2020.3034153;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9240982;2021;TL;Accuracy;FRUIT;;Raspberry Pi;
S173 ; Toward Edge-Assisted Video Content Intelligent Caching With Long Short-Term Memory Learning;10.1109/ACCESS.2019.2947067;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8866710;2019;LSTM;Accuracy;CIFAR-10;;;
S174 ; Toward Edge-Based Deep Learning in Industrial Internet of Things;10.1109/JIOT.2019.2963635;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8948000;2020;LeNet, VGG;Accuracy;OTROS;;;
S175 ; Toward Intelligent Surveillance as an Edge Network Service (iSENSE) using Lightweight Detection and Tracking Algorithms;10.1109/TSC.2019.2916416;1939-1374;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8713550;2019;CNN, MobileNet, GOOGLE NET, SVM;False Negative Rate, False Positive Rate;OTROS;;Raspberry Pi;
S176 ; Toward Intelligent Task Offloading at the Edge;10.1109/MNET.001.1900200;1558-156X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8884234;2020;DT, C4.5;Accuracy;CIFAR-10;;;Wireless, 4G/5G, Otro
S177 ; Toward ML/AI-Based Prediction of Mobile Service Usage in Next-Generation Networks;10.1109/MNET.001.1900462;1558-156X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9048615;2020;SVM, J48, RF, KNN, NB;Accuracy;OTROS;;;
S178 ; Toward Resource-Efficient Federated Learning in Mobile Edge Computing;10.1109/MNET.011.2000295;1558-156X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9354925;2021;CNN, LSTM, FL;Decay Rate;MNIST;;;
S179 ; Towards an IoT-based Deep Learning Architecture for Camera Trap Image Classification;10.1109/GCAIoT51063.2020.9345858;;978-1-7281-8420-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9345858;2020;DENSENET, MobileNet, Inception, ResNet;Accuracy, F-measure;OTROS;;Raspberry Pi;
S180 ; Towards an Machine Learning-Based Edge Computing Oriented Monitoring System for the Desert Border Surveillance Use Case;10.1109/ACCESS.2020.3042699;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9281292;2020;SVM, DT, KNN, NB;Accuracy, F-measure, Precision, Recall;OTROS;;;
S181 ; Towards Blockchain-Based Reputation-Aware Federated Learning;10.1109/INFOCOMWKSHPS50562.2020.9163027;;978-1-7281-8695-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9163027;2020;FL;;;;;
S182 ; Towards Designing an Adaptive Framework for Facial Image Quality Estimation at Edge;10.1109/I2CT.2018.8529475;;978-1-5386-4273-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8529475;2018;CNN, SVM, DT, RF, KNN;Accuracy, ROC, F-measure;CIFAR-10, MNIST, PASCAL;;;
S183 ; Towards Edge Computing Based Distributed Data Analytics Framework in Smart Grids;10.1007/978-3-030-24274-9_25;;;http://link.springer.com/chapter/10.1007/978-3-030-24274-9_25;2019;CNN;Cross Validation;OTROS;;;
S184 ; Towards Scalable Video Analytics at the Edge;10.1109/SAHCN.2019.8824876;2155-5494;978-1-7281-1207-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8824876;2019;VGG;Precision;;;;
S185 ; Towards Ubiquitous Intelligent Computing: Heterogeneous Distributed Deep Neural Networks;10.1109/TBDATA.2018.2880978;2332-7790;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8543852;2018;MobileNet, ResNet;;CIFAR-10;;;
S186 ; TrafficChain: A Blockchain-Based Secure and Privacy-Preserving Traffic Map;10.1109/ACCESS.2020.2980298;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9034098;2020;LSTM, RNN, LiR, LoR;;OTROS;;;
S187 ; Training Deep Neural Networks with Constrained Learning Parameters;10.1109/ICRC2020.2020.00018;;978-0-7381-4337-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9325350;2020;AlexNet, LeNet, MLP , RL;Errors;DIGITS;;;
S188 ; Tree-Based Deep Networks for Edge Devices;10.1109/TII.2019.2950326;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8886463;2020;VGG, MobileNet, ResNet;Accuracy, Otro;CIFAR-10;;;
S189 ; Trust-Based Social Networks with Computing, Caching and Communications: A Deep Reinforcement Learning Approach;10.1109/TNSE.2018.2865183;2327-4697;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8434316;2020;DRL;;;;;
S190 ; UAV based cost-effective real-time abnormal event detection using edge computing;10.1007/s11042-019-08067-1;;;http://link.springer.com/article/10.1007/s11042-019-08067-1;2019;YOLO;Accuracy, F-measure, Precision, Recall;CIFAR-10, PASCAL;;Raspberry Pi;
S191 ; UAV-assisted Real-time Data Processing using Deep Q-Network for Industrial Internet of Things;10.1109/ICAIIC48513.2020.9065203;;978-1-7281-4985-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9065203;2020;DQN;;;;;
S192 ; UbeHealth: A Personalized Ubiquitous Cloud and Edge-Enabled Networked Healthcare System for Smart Cities;10.1109/ACCESS.2018.2846609;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8382164;2018;LSTM, RNN;;;;;4G/5G
S193 ; Ubiquitous Distributed Deep Reinforcement Learning at the Edge: Analyzing Byzantine Agents in Discrete Action Spaces;https://doi.org/10.1016/j.procs.2020.10.043;1877-0509;;https://www.sciencedirect.com/science/article/pii/S1877050920323115;2020;DRL;;;;;4G/5G
S194 ; Urban Intelligence With Deep Edges;10.1109/ACCESS.2020.2963912;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8949510;2020;CNN, VGG;Accuracy, ROC, F-measure, Precision, Recall;CIFAR-10, MNIST, PASCAL;;Raspberry Pi;
S195 ; Urban Street Cleanliness Assessment Using Mobile Edge Computing and Deep Learning;10.1109/ACCESS.2019.2914270;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8704340;2019;CNN;Accuracy;IMAGENET;;;
S196 ; UrbanEdge: Deep Learning Empowered Edge Computing for Urban IoT Time Series Prediction;10.1145/3321408.3323089;9.78E+12;;https://doi.org/10.1145/3321408.3323089;2019;LSTM, RNN;MAPE, RMSE;;;;
S197 ; Use of Machine Learning in Detecting Network Security of Edge Computing System;10.1109/ICBDA.2019.8713237;;978-1-7281-1282-4;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8713237;2019;RBF, SVM;Accuracy, Cross Validation;CIFAR-10, OTROS;;;
S198 ; Using BPM Technology to Deploy and Manage Distributed Analytics in Collaborative IoT-Driven Business Scenarios;10.1145/3365871.3365890;9.78E+12;;https://doi.org/10.1145/3365871.3365890;2019;MLP ;;;;Raspberry Pi;
S199 ; Verifiable Edge Computing for Indoor Positioning;10.1109/ICC40277.2020.9148819;1938-1883;978-1-7281-5089-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9148819;2020;MLP , SVM, RF, KNN;Accuracy;DIGITS;;;
S200 ; Video Sensor Security System in IoT Based on Edge Computing;10.1109/WCSP49889.2020.9299709;2472-7628;978-1-7281-7236-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9299709;2020;DNN;;OTROS;;Raspberry Pi;
S201 ; Voice Pathology Detection Using Deep Learning on Mobile Healthcare Framework;10.1109/ACCESS.2018.2856238;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8411437;2018;VGG;Accuracy, Sensitivity, Specificity;OTROS;;;
S202 ; When Deep Learning Meets the Edge: Auto-Masking Deep Neural Networks for Efficient Machine Learning on Edge Devices;10.1109/ICCD46524.2019.00076;2576-6996;978-1-5386-6648-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8988678;2019;DENSENET, VGG, ResNet;Otro;IMAGENET;Batería;;
S203 ; When Deep Reinforcement Learning Meets Federated Learning: Intelligent Multitimescale Resource Management for Multiaccess Edge Computing in 5G Ultradense Network;10.1109/JIOT.2020.3026589;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9205252;2021;DRL, DQL, DQN;;;;;
S204 ; Where is my Deer?-Wildlife Tracking And Counting via Edge Computing And Deep Learning;10.1109/SENSORS47125.2020.9278802;2168-9229;978-1-7281-6801-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9278802;2020;YOLO;Errors;DIGITS;;;Otro
S205 ; Wireless Data Acquisition for Edge Learning: Importance-Aware Retransmission;10.1109/SPAWC.2019.8815498;1948-3252;978-1-5386-6528-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8815498;2019;SVM;Accuracy;MNIST;;;Wireless
S206 ; Wireless Distributed Edge Learning: How Many Edge Devices Do We Need?;10.1109/JSAC.2020.3041379;1558-0008;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9276433;2020;DML;;OTROS;;;Wireless
S207 ; Wireless Edge Machine Learning: Resource Allocation and Trade-offs;10.1109/ACCESS.2021.3066559;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9380634;2021;MLP , SVM;Mean Squared Deviation;MNIST;Batería;;
S208 ; WorkerFirst: Worker-Centric Model Selection for Federated Learning in Mobile Edge Computing;10.1109/ICCC49849.2020.9238867;2377-8644;978-1-7281-7327-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9238867;2020;LSTM, DRL, DQL, DQN, FL;;;;;Wireless
S209 ; Work-in-Progress: Enabling Edge-based Self-Navigation in Earthquake-Struck Zones;10.1109/CODESISSS51650.2020.9244030;;978-1-7281-9198-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9244030;2020;AlexNet, VGG, FCN/FRCNN, ERFNET, SegNet, ENET;;PASCAL;Batería;Otro;
S210 ; ZyNet: Automating Deep Neural Network Implementation on Low-Cost Reconfigurable Edge Computing Platforms;10.1109/ICFPT47387.2019.00058;;978-1-7281-2943-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8977883;2019;DNN;Accuracy;MNIST;;Raspberry Pi;
S211 ; 14.4 All-Digital Time-Domain CNN Engine Using Bidirectional Memory Delay Lines for Energy-Efficient Edge Computing;10.1109/ISSCC.2019.8662510;2376-8606;978-1-5386-8531-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8662510;2019;AlexNet, LeNet;Accuracy;CIFAR-10;Continua;Otro;
S212 ; 3D Semantic Map Construction Using Improved ORB-SLAM2 for Mobile Robot in Edge Computing Environment;10.1109/ACCESS.2020.2983488;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9047931;2020;SkipNet, BAFF-SkipNet;Accuracy;CIFAR-10;;Otro;
S213 ; A 12.08-TOPS/W All-Digital Time-Domain CNN Engine Using Bi-Directional Memory Delay Lines for Energy Efficient Edge Computing;10.1109/JSSC.2019.2939888;1558-173X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8867969;2020;Inception;ROC, Recall;MNIST;;Raspberry Pi;
S214 ; A 34-FPS 698-GOP/s/W Binarized Deep Neural Network-Based Natural Scene Text Interpretation Accelerator for Mobile Edge Computing;10.1109/TIE.2018.2875643;1557-9948;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8513982;2019;CNN, MobileNet;Accuracy;CIFAR-10;;Raspberry Pi;
S215 ; A 65-nm Neuromorphic Image Classification Processor With Energy-Efficient Training Through Direct Spike-Only Feedback;10.1109/JSSC.2019.2942367;1558-173X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8867974;2020;YOLO;MAP, Recall;;;Jetson NX Xavier;
S216 ; A Current Mirror Cross Bar Based 2.86-TOPS/W Machine Learner and PUF with <2.5% BER in 65nm CMOS for IoT Application;10.1109/ISCAS.2019.8702441;2158-1525;978-1-7281-0397-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8702441;2019;ELM;Errors;MNIST;;;
S217 ; A Deep Learning Model Generation Framework for Virtualized Multi-Access Edge Cache Management;10.1109/ACCESS.2019.2916080;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8712457;2019;DNN, CNN, SVM, RF;Accuracy, F-measure;OTROS;;;
S218 ; A Directional Gamma-Ray Spectrometer With Microcontroller-Embedded Machine Learning;10.1109/JETCAS.2020.3029570;2156-3365;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9217446;2020;ANN, SVM;Accuracy;OTROS;;;
S219 ; A Facial Expression Recognition Method Using Deep Convolutional Neural Networks Based on Edge Computing;10.1109/ACCESS.2020.2980060;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9032142;2020;YOLO;Precision;PASCAL;;;
S220 ; A Fog-Augmented Machine Learning based SMS Spam Detection and Classification System;10.1109/FMEC49853.2020.9144833;;978-1-7281-7216-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9144833;2020;VGG, MobileNet, Inception;Accuracy;CIFAR-10;;Raspberry Pi;
S221 ; A Fully Embedded Adaptive Real-Time Hand Gesture Classifier Leveraging HD-sEMG and Deep Learning;10.1109/TBCAS.2019.2955641;1940-9990;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8911244;2020;ANN, LoR;Accuracy;CIFAR-10;;;
S222 ; A Lightweight Short-Term Photovoltaic Power Prediction for Edge Computing;10.1109/TGCN.2020.2996234;2473-2400;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9097945;2020;DRL;;;;;
S223 ; A Low-Power Embedded System for Real-Time sEMG based Event-Driven Gesture Recognition;10.1109/ICECS46596.2019.8964944;;978-1-7281-0996-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8964944;2019;ANN;Accuracy, F-measure, Precision, Recall;CIFAR-10, PASCAL;;;
S224 ; A Machine Learning Framework for Edge Computing to Improve Prediction Accuracy in Mobile Health Monitoring;10.1007/978-3-030-24302-9_30;;;http://link.springer.com/chapter/10.1007/978-3-030-24302-9_30;2019;CNN, SVM;Accuracy;MNIST, DIGITS;;Raspberry Pi;Wi-Fi
S225 ; A MobileNets Convolutional Neural Network for GIS Partial Discharge Pattern Recognition in the Ubiquitous Power Internet of Things Context: Optimization, Comparison, and Application;10.1109/ACCESS.2019.2946662;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8865063;2019;AlexNet, LeNet, CNN, BPNN, VGG, ResNet, DT;Recognition Rate, Otro;;;;
S226 ; A New Vehicular Fog Computing Architecture for Cooperative Sensing of Autonomous Driving;10.1109/ACCESS.2020.2964029;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8950168;2020;AlexNet, VGG;Accuracy;OTROS;Continua;Jetson TX2;Wireless
S227 ; A Non-Intrusive Multi-Parameter Fault Diagnosis System for Industrial Machineries;10.1109/PADSW.2018.8644893;1521-9097;978-1-5386-7308-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8644893;2018;MobileNet, YOLO;MAP;;;Jetson TX2;
S228 ; A Novel Approach for Service Function Chain Dynamic Orchestration in Edge Clouds;10.1109/LCOMM.2020.3000588;1558-2558;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9110551;2020;CNN, MLP , ResNet;Accuracy;CIFAR-10;;Otro;
S229 ; A Novel Architecture for Condition Based Machinery Health Monitoring on Marine Vessels Using Deep Learning and Edge Computing;10.1109/ISMCR47492.2019.8955729;;978-1-7281-4899-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8955729;2019;CNN;;;;;
S230 ; A Novel Hierarchical Edge Computing Solution Based on Deep Learning for Distributed Image Recognition in IoT Systems;10.1109/INCIT.2019.8912138;;978-1-7281-1019-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8912138;2019;CNN;;;;;
S231 ; A ReRAM-Based Computing-in-Memory Convolutional-Macro With Customized 2T2R Bit-Cell for AIoT Chip IP Applications;10.1109/TCSII.2020.3013336;1558-3791;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9179148;2020;AlexNet;;;USB;Raspberry Pi;
S232 ; A Rigorous Analysis of Biomedical Edge Computing: An Arrhythmia Classification Use-Case Leveraging Deep Learning;10.1109/IoTaIS50849.2021.9359721;;978-1-7281-9448-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9359721;2021;;Accuracy;CIFAR-10;;;
S233 ; A Robust Deep-Neural-Network-Based Compressed Model for Mobile Device Assisted by Edge Server;10.1109/ACCESS.2019.2958406;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8928622;2019;ANN;Accuracy;CIFAR-10;;;
S234 ; A self-adaptive approach to service deployment under mobile edge computing for autonomous driving;https://doi.org/10.1016/j.engappai.2019.03.006;0952-1976;;https://www.sciencedirect.com/science/article/pii/S0952197619300491;2019;CNN, LSTM, MLP ;MAP;OTROS;;Raspberry Pi, Jetson TX2;
S235 ; A Situation Enabled Framework for Energy-Efficient Workload Offloading in 5G Vehicular Edge Computing;10.1109/SERVICES48979.2020.00027;2642-939X;978-1-7281-8203-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9284171;2020;YOLO;MAP;FRUIT;;Jetson TX2;
S236 ; A Smart Classroom Based on Deep Learning and Osmotic IoT Computing;10.1109/CONIITI.2018.8587095;;978-1-5386-8131-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8587095;2018;CNN;;;;;
S237 ; A Support Infrastructure for Machine Learning at the Edge in Smart City Surveillance;10.1109/ISCC47284.2019.8969779;2642-7389;978-1-7281-2999-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8969779;2019;DNN, ANN, RL, DT, RT, RF, GBT;;;;;
S238 ; A Vector Mosquitoes Classification System Based on Edge Computing and Deep Learning;10.1109/TAAI.2018.00015;2376-6824;978-1-7281-1229-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8588471;2018;CNN;Accuracy;CIFAR-10;;;
S239 ; Accelerating Gossip-Based Deep Learning in Heterogeneous Edge Computing Platforms;10.1109/TPDS.2020.3046440;1558-2183;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9303468;2021;MLP ;Accuracy;OTROS;;Raspberry Pi;
S240 ; Accelerating Mobile Applications at the Network Edge with Software-Programmable FPGAs;10.1109/INFOCOM.2018.8485850;;978-1-5386-4128-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8485850;2018;ANN, SVM, RF, KNN;Accuracy;OTROS;Batería;Raspberry Pi;
S241 ; Accuracy vs. traffic trade-off of learning IoT data patterns at the edge with hypothesis transfer learning;10.1109/RTSI.2016.7740634;;978-1-5090-1131-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7740634;2016;TL, SVM;Loss Rate;OTROS;;;
S242 ; Achieving Democracy in Edge Intelligence: A Fog-Based Collaborative Learning Scheme;10.1109/JIOT.2020.3020911;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9184072;2021;MLP , SVM, DT, KNN, NB;Accuracy;CIFAR-10;;;
S243 ; Adaptive Critical Care Intervention in the Internet of Medical Things;10.1109/EAIS48028.2020.9122762;2473-4691;978-1-7281-4384-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9122762;2020;SVM;Accuracy;OTROS;;;
S244 ; Adaptive Federated Learning in Resource Constrained Edge Computing Systems;10.1109/JSAC.2019.2904348;1558-0008;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8664630;2019;CNN, SVM, K-means, LiR;Accuracy, Loss Rate;CIFAR-10, MNIST;;;
S245 ; ADELE: An Architecture for Steering Traffic and Computations via Deep Learning in Challenged Edge Networks;10.1109/CCCS.2019.8888120;;978-1-7281-0875-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8888120;2019;DNN, LSTM;;;;;
S246 ; Advanced Deep Learning-Based Computational Offloading for Multilevel Vehicular Edge-Cloud Computing Networks;10.1109/ACCESS.2020.3011705;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9146836;2020;;;OTROS;;;
S247 ; Age & Gender Classifier for Edge Computing;10.1109/MECO.2019.8760160;2637-9511;978-1-7281-1740-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8760160;2019;DNN;;;;;
S248 ; Age Estimation Using Aging/Rejuvenation Features With Device-Edge Synergy;10.1109/TCSVT.2020.2981117;1558-2205;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9037298;2021;RNN, GRU, YOLO;Accuracy;CIFAR-10;;Raspberry Pi;Wi-Fi
S249 ; Agent grouping recommendation method in edge computing;10.1007/s12652-019-01658-8;;;http://link.springer.com/article/10.1007/s12652-019-01658-8;2020;CNN, SVM, RF;Accuracy, F-measure, Precision;OTROS;;Raspberry Pi, Jetson Nano ;
S250 ; Agriculture Management Based on LoRa Edge Computing System;10.1007/978-3-030-66471-8_10;;;http://link.springer.com/chapter/10.1007/978-3-030-66471-8_10;2020;MobileNet;;;;;
S251 ; AI-based Customer Behavior Analytics System using Edge Computing Device;10.1109/ICEIC49074.2020.9051138;;978-1-7281-6289-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9051138;2020;RF, GBT;Accuracy;CIFAR-10;;;
S252 ; AI-Enhanced Offloading in Edge Computing: When Machine Learning Meets Industrial IoT;10.1109/MNET.001.1800510;1558-156X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8863729;2019;TL;;OTROS;;;
S253 ; Algorithmic implementation of deep learning layer assignment in edge computing based smart city environment;https://doi.org/10.1016/j.compeleceng.2020.106909;0045-7906;;https://www.sciencedirect.com/science/article/pii/S0045790620307618;2021;;ROC;MNIST;;;4G/5G
S254 ; An Accurate EEGNet-based Motor-Imagery Brain–Computer Interface for Low-Power Edge Computing;10.1109/MeMeA49120.2020.9137134;;978-1-7281-5386-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9137134;2020;DNN;;;;;
S255 ; An Agent based Resource Provision for IoT through Machine Learning in Fog Computing;10.1109/ICSCAN.2019.8878821;;978-1-7281-1525-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8878821;2019;RL;;;;;
S256 ; An AI-Enabled Three-Party Game Framework for Guaranteed Data Privacy in Mobile Edge Crowdsensing of IoT;10.1109/TII.2019.2957130;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8918437;2021;C4.5;;;;;
S257 ; An autonomous computation offloading strategy in Mobile Edge Computing: A deep learning-based hybrid approach;https://doi.org/10.1016/j.jnca.2021.102974;1084-8045;;https://www.sciencedirect.com/science/article/pii/S1084804521000011;2021;LSTM, MLP ;MAE, RMSE;;;;
S258 ; An Edge Computing Framework for Real-Time Monitoring in Smart Grid;10.1109/ICII.2018.00019;;978-1-5386-7771-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8539108;2018;DNN;;;;;
S259 ; An Edge-Assisted and Smart System for Real-Time Pain Monitoring;10.1109/CHASE48038.2019.00023;;978-1-7281-4687-4;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8908653;2019;ResNet;ROC;CIFAR-10, IMAGENET;;Otro;
S260 ; An Effective Training Scheme for Deep Neural Network in Edge Computing Enabled Internet of Medical Things (IoMT) Systems;10.1109/ACCESS.2020.3000322;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9109259;2020;CNN;Accuracy, False Negative Rate, False Positive Rate, Precision, Sensitivity;OTROS;;;Wireless
S261 ; An efficient approach for rice prediction from authenticated Block chain node using machine learning technique;https://doi.org/10.1016/j.eti.2020.101064;2352-1864;;https://www.sciencedirect.com/science/article/pii/S235218642031364X;2020;LSTM;;COCO;;;
S262 ; An energy efficient IoT data compression approach for edge machine learning;https://doi.org/10.1016/j.future.2019.02.005;0167-739X;;https://www.sciencedirect.com/science/article/pii/S0167739X18331716;2019;MobileNet, ResNet, QL ES RL;Accuracy, F-measure, Precision, Recall;OTROS;;;
S263 ; An Entire-and-Partial Feature Transfer Learning Approach for Detecting the Frequency of Pest Occurrence;10.1109/ACCESS.2020.2992520;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9086469;2020;CNN, RF, GBT, LoR, NB;Accuracy, F-measure, Precision, Recall;OTROS;;;
S264 ; An Improved Chaotic Bat Swarm Scheduling Learning Model on Edge Computing;10.1109/ACCESS.2019.2914261;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8704178;2019;LSTM;;;;;
S265 ; An intelligent task offloading algorithm (iTOA) for UAV edge computing network;https://doi.org/10.1016/j.dcan.2020.04.008;2352-8648;;https://www.sciencedirect.com/science/article/pii/S2352864819303037;2020;ANN, DT;ROC;MNIST;;;
S266 ; An Optimized Face Recognition for Edge Computing;10.1109/ASICON47005.2019.8983596;2162-755X;978-1-7281-0735-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8983596;2019;DQN;;;;;Wireless
S267 ; Analysis of High Frequency Data of a Machine Tool via Edge Computing;https://doi.org/10.1016/j.promfg.2020.04.028;2351-9789;;https://www.sciencedirect.com/science/article/pii/S2351978920310660;2020;;Otro;;Continua;Arduino;Wi-Fi
S268 ; Animation Rendering on Multimedia Fog Computing Platforms;10.1109/CloudCom.2016.0060;2330-2186;978-1-5090-1445-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7830701;2016;ANN, LSTM;RMSE;;;Arduino, Jetson NX Xavier;
S269 ; Anomaly Detection in Smart Environments using AI over Fog and Cloud Computing;10.1109/CCNC49032.2021.9369449;2331-9860;978-1-7281-9794-4;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9369449;2021;YOLO;;;;Raspberry Pi, Otro;Wi-Fi
S270 ; Anomaly detection on the edge;10.1109/MILCOM.2017.8170817;2155-7586;978-1-5386-0595-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8170817;2017;CNN;;IMAGENET;;Jetson TX2;
S271 ; Application of Edge Intelligent Computing in Satellite Internet of Things;10.1109/SmartIoT.2019.00022;;978-1-7281-3488-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8896440;2019;CNN, VGG, MobileNet, Inception, ResNet;;;;;
S272 ; Application of video analysis based on mobile edge computing;10.1109/CompComm.2017.8322895;;978-1-5090-6352-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8322895;2017;CNN, VGG;;OTROS;;;
S273 ; Are Existing Knowledge Transfer Techniques Effective for Deep Learning with Edge Devices?;10.1109/EDGE.2018.00013;;978-1-5386-7238-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8473375;2018;DRL;;;;;4G/5G
S274 ; Area Constraint Aware Physical Unclonable Function for Intelligence Module;10.1109/ICCIA.2018.00046;;978-1-5386-9571-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8711523;2018;ANN;;;;;
S275 ; Artificial Intelligence and Deep Learning Applications for Automotive Manufacturing;10.1109/BigData.2018.8622357;;978-1-5386-5035-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8622357;2018;QL ES RL;;;Solar;;
S276 ; Artificial Intelligence Empowered UAVs Data Offloading in Mobile Edge Computing;10.1109/ICC40277.2020.9149115;1938-1883;978-1-7281-5089-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9149115;2020;;;;;;
S277 ; Artificial Intelligence-Powered Mobile Edge Computing-Based Anomaly Detection in Cellular Networks;10.1109/TII.2019.2953201;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8896997;2020;CNN;Accuracy, Errors, F-measure, False Positive Rate, Precision, Recall, Otro;OTROS;;;
S278 ; Assistive Technology through Internet of Things and Edge Computing;10.1109/ICCE-Berlin47944.2019.8966148;2166-6822;978-1-7281-2745-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8966148;2019;DNN;;;;;
S279 ; Automated Labeling and Learning for Physical Layer Authentication Against Clone Node and Sybil Attacks in Industrial Wireless Edge Networks;10.1109/TII.2020.2963962;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8960424;2021;MobileNet, Inception;Accuracy;CIFAR-10;;Raspberry Pi;
S280 ; Benchmarking GPU-Accelerated Edge Devices;10.1109/BigComp48618.2020.00-89;2375-9356;978-1-7281-6034-4;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9070647;2020;LeNet, MLP , ResNet, GOOGLE NET;Accuracy;CIFAR-10, MNIST, IMAGENET;;;
S281 ; Big Data Cleaning Based on Mobile Edge Computing in Industrial Sensor-Cloud;10.1109/TII.2019.2938861;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8822503;2020;RNN, MobileNet, Inception, ResNet;Errors;OTROS;;;
S282 ; Blockchain and Learning-Based Secure and Intelligent Task Offloading for Vehicular Fog Computing;10.1109/TITS.2020.3007770;1558-0016;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9145846;2020;CNN;Accuracy;CIFAR-10;;Raspberry Pi;
S283 ; Blockchain-Based Edge Computing for Deep Neural Network Applications;10.1145/3285017.3285027;9.78E+12;;https://doi.org/10.1145/3285017.3285027;2018;MobileNet;MAP;PASCAL;;Raspberry Pi;Bluetooth, Wi-Fi
S284 ; Body weight estimation of yak based on cloud edge computing;10.1186/s13638-020-01879-y;;;http://link.springer.com/article/10.1186/s13638-020-01879-y;2021;LSTM;ROC;MNIST;Batería;Jetson NX Xavier;
S285 ; BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systems;10.1109/ICCWorkshops49005.2020.9145068;2474-9133;978-1-7281-7440-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9145068;2020;;Accuracy;CIFAR-10;;Raspberry Pi;Wi-Fi
S286 ; Bringing Deep Learning at the Edge of Information-Centric Internet of Things;10.1109/LCOMM.2018.2875978;1558-2558;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8491360;2019;CNN, RNN, SVM, RL, LiR, SVR;;;;;
S287 ; Buffer Management in Online Kernel Machines;10.1109/CCECE.2018.8447535;2576-7046;978-1-5386-2410-4;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8447535;2018;SVM, SOKML, KLMS;Accuracy;MNIST;;;
S288 ; Building and Evaluating Federated Models for Edge Computing;10.23919/CNSM50824.2020.9269105;2165-963X;978-3-903176-31-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9269105;2020;LSTM;Otro;OTROS;;;Wi-Fi
S289 ; CamThings: IoT Camera with Energy-Efficient Communication by Edge Computing based on Deep Learning;10.1109/ATNAC.2018.8615368;2474-154X;978-1-5386-7177-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8615368;2018;DNN;;;;;
S290 ; Cardio Twin: A Digital Twin of the human heart running on the edge;10.1109/MeMeA.2019.8802162;;978-1-5386-8428-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8802162;2019;CNN, SVM, RF;Accuracy, Cross Validation, R2, Otro;CIFAR-10, OTROS;;;
S291 ; Cartel: A System for Collaborative Transfer Learning at the Edge;10.1145/3357223.3362708;9.78E+12;;https://doi.org/10.1145/3357223.3362708;2019;LSTM, GRU;R2, Otro;CIFAR-10;;;
S292 ; CEML: Mixing and Moving Complex Event Processing and Machine Learning to the Edge of the Network for IoT Applications;10.1145/2991561.2991575;9.78E+12;;https://doi.org/10.1145/2991561.2991575;2016;IL;;;;;
S293 ; CityFlow: Supporting Spatial-Temporal Edge Computing for Urban Machine Learning Applications;10.1007/978-3-030-28925-6_1;;;http://link.springer.com/chapter/10.1007/978-3-030-28925-6_1;2020;CNN, LSTM, MLP ;;CIFAR-10, MNIST;;Raspberry Pi;
S294 ; Cloud-Edge Collaboration Framework for IoT data analytics;10.1109/ICTC.2018.8539664;2162-1233;978-1-5386-5041-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8539664;2018;ML;;;;;
S295 ; CMix-NN: Mixed Low-Precision CNN Library for Memory-Constrained Edge Devices;10.1109/TCSII.2020.2983648;1558-3791;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9049084;2020;CNN;Accuracy, ROC;CIFAR-10, MNIST;;;4G/5G
S296 ; Cognitive Balance for Fog Computing Resource in Internet of Things: An Edge Learning Approach;10.1109/TMC.2020.3026580;1558-0660;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9205577;2020;CNN, FL;Accuracy;MNIST;;Raspberry Pi;
S297 ; Cognitive edge computing through artificial intelligence;10.1109/COMM48946.2020.9142010;;978-1-7281-5611-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9142010;2020;CNN;;CIFAR-10, MNIST;;;
S298 ; Cognitive multi-agent empowering mobile edge computing for resource caching and collaboration;https://doi.org/10.1016/j.future.2019.08.001;0167-739X;;https://www.sciencedirect.com/science/article/pii/S0167739X19318783;2020;LeNet, VGG, Inception;;;;;
S299 ; Collaborative Edge Computing With FPGA-Based CNN Accelerators for Energy-Efficient and Time-Aware Face Tracking System;10.1109/TCSS.2021.3059318;2329-924X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9363321;2021;LSTM, SVM, DT;ROC;MNIST;;;
S300 ; Communication, Computing, and Learning on the Edge;10.1109/ICCS.2018.8689229;;978-1-5386-7864-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8689229;2018;FACENET;Accuracy;OTROS;;;
S301 ; Communication-Efficient Federated Learning for Wireless Edge Intelligence in IoT;10.1109/JIOT.2019.2956615;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8917724;2020;FL;Accuracy;CIFAR-10, MNIST;;;
S302 ; Comparing SVM and SSD for classification of vehicles and pedestrians for edge computing;10.1109/ColCACI.2019.8781989;;978-1-7281-1614-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8781989;2019;FCN/FRCNN;Accuracy, Precision, Recall;OTROS;;;
S303 ; Computation Offloading for Fast CNN Inference in Edge Computing;10.1145/3338840.3355669;9.78E+12;;https://doi.org/10.1145/3338840.3355669;2019;ANN, RNN, SVM, RT;Accuracy;CIFAR-10;;;
S304 ; Computation Offloading for Machine Learning Web Apps in the Edge Server Environment;10.1109/ICDCS.2018.00154;2575-8411;978-1-5386-6871-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8416417;2018;QL ES RL;;;;;4G/5G
S305 ; Computation offloading for mobile edge computing: A deep learning approach;10.1109/PIMRC.2017.8292514;2166-9589;978-1-5386-3531-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8292514;2017;LoR, NB;Accuracy;OTROS;;;
S306 ; Computation Offloading in Multi-Access Edge Computing Networks: A Multi-Task Learning Approach;10.1109/ICC.2019.8761212;1938-1883;978-1-5386-8088-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8761212;2019;DQN, QL ES RL;;;;;
S307 ; Computational Offloading for CNN-based Toxic Comment Detection on a Smartwatch;10.1109/FMEC49853.2020.9144770;;978-1-7281-7216-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9144770;2020;CNN;Accuracy, F-measure, Precision, Recall;CIFAR-10, PASCAL;;Otro;
S308 ; Computational Resource Allocation for Edge Computing in Social Internet-of-Things;10.1109/MWSCAS48704.2020.9184663;1558-3899;978-1-7281-8058-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9184663;2020;CNN, LSTM, SVM;;OTROS;;Raspberry Pi, Jetson Nano , Otro;
S309 ; Computing and Processing on the Edge: Smart Pathology Detection for Connected Healthcare;10.1109/MNET.001.1900045;1558-156X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8933558;2019;CNN, SVM, KNN;Recall;OTROS;;Jetson Nano ;
S310 ; Computing aware scheduling in mobile edge computing system;10.1007/s11276-018-1892-z;;;http://link.springer.com/article/10.1007/s11276-018-1892-z;2019;ELM;Accuracy;CIFAR-10;;;
S311 ; Confidential information protection method of commercial information physical system based on edge computing;10.1007/s00521-020-05272-0;;;http://link.springer.com/article/10.1007/s00521-020-05272-0;2021;SVM;False Negative Rate, False Positive Rate;;;;4G/5G
S312 ; Congestion-aware adaptive decentralised computation offloading and caching for multi-access edge computing networks;https://doi.org/10.1049/iet-com.2020.0630; ;;https://onlinelibrary.wiley.com/doi/abs/10.1049/iet-com.2020.0630;2020;AlexNet, CNN, SegNet;Recall;;;;Wireless
S313 ; Context-Aware Object Detection for Vehicular Networks Based on Edge-Cloud Cooperation;10.1109/JIOT.2019.2949633;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8883194;2020;R-CNN;;OTROS;;;
S314 ; Conversion of Artificial Neural Network to Spiking Neural Network for Hardware Implementation;10.1109/ICCE-TW46550.2019.8991758;;978-1-7281-3279-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8991758;2019;;Accuracy;CIFAR-10;;;
S315 ; Crowdtraining: Architecture and Incentive Mechanism for Deep Learning Training in the Internet of Things;10.1109/MNET.001.1800498;1558-156X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8863732;2019;RL;;IMAGENET;;;
S316 ; Data Augmentation and Deep Learning Modeling Methods on Edge-Device-Based Sign Language Recognition;10.1109/ISCTT51595.2020.00093;;978-1-7281-8575-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9363839;2020;DNN, CNN, ANN, LSTM, RNN, GRU;;OTROS;;Raspberry Pi;
S317 ; Data Driven Service Orchestration for Vehicular Networks;10.1109/TITS.2020.3011264;1558-0016;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9153150;2020;ANN;;;;;
S318 ; Data-Importance Aware Radio Resource Allocation: Wireless Communication Helps Machine Learning;10.1109/LCOMM.2020.2996605;1558-2558;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9098940;2020;MobileNet;Accuracy;OTROS;;;
S319 ; Deep anomaly detection in expressway based on edge computing and deep learning;10.1007/s12652-020-02574-y;;;http://link.springer.com/article/10.1007/s12652-020-02574-y;2020;;ROC;MNIST;;;
S320 ; Deep Learning and Edge Computing Solutions for High Performance Computing;10.1007/978-3-030-60265-9;;;http://link.springer.com/book/10.1007/978-3-030-60265-9;2021;ANN;Otro;;;;
S321 ; Deep Learning Based Couple-like Cooperative Computing Method for IoT-based Intelligent Surveillance Systems;10.1109/PIMRC.2019.8904229;2166-9589;978-1-5386-8110-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8904229;2019;CNN;;;;;
S322 ; Deep Learning Based Pathology Detection for Smart Connected Healthcare;10.1109/MNET.011.2000064;1558-156X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9165267;2020;ResNet;Accuracy;COCO, PASCAL;;;
S323 ; Deep Learning Based Sensing Resource Allocation for Mobile Target Tracking;10.1109/ICCT50939.2020.9295877;2576-7828;978-1-7281-8141-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9295877;2020;FL;Accuracy;CIFAR-10;;;
S324 ; Deep Learning Empowered Task Offloading for Mobile Edge Computing in Urban Informatics;10.1109/JIOT.2019.2903191;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8660505;2019;QL ES RL;;;;;
S325 ; Deep Learning for Secure Mobile Edge Computing in Cyber-Physical Transportation Systems;10.1109/MNET.2019.1800458;1558-156X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8782874;2019;LeNet, DENSENET, ResNet;Accuracy;CIFAR-10;;;
S326 ; Deep Learning for Service Function Chain Provisioning in Fog Computing;10.1109/ACCESS.2020.3021355;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9187676;2020;DENSENET, VGG, MobileNet, Inception, ResNet;;;;;
S327 ; Deep Learning for Smart Industry: Efficient Manufacture Inspection System With Fog Computing;10.1109/TII.2018.2842821;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8370640;2018;CNN;False Positive Rate, Otro;;;;
S328 ; Deep Learning in Resource and Data Constrained Edge Computing Systems;10.1007/978-3-662-62746-4_5;;;http://link.springer.com/chapter/10.1007/978-3-662-62746-4_5;2021;CNN, KNN;;;;;
S329 ; Deep Learning in the Era of Edge Computing: Challenges and Opportunities;10.1002/9781119551713.ch3;;9.78E+12;https://ieeexplore.ieee.org/xpl/ebooks/bookPdfWithBanner.jsp?fileName=9116726.pdf&bkn=9116611&pdfType=chapter;2020;RL;;;;Raspberry Pi;
S330 ; Deep Learning in the Era of Edge Computing: Challenges and Opportunities A crosswalk pedestrian recognition system by using deep learning and zebra-crossing recognition techniques;https://doi.org/10.1002/spe.2742;9.78E+12;;https://onlinelibrary.wiley.com/doi/abs/10.1002/spe.2742;2020;YOLO;Accuracy;OTROS;;;
S331 ; Deep Learning in the Era of Edge Computing: Challenges and Opportunities Proactive content caching by exploiting transfer learning for mobile edge computing;https://doi.org/10.1002/dac.3706;9.78E+12;;https://onlinelibrary.wiley.com/doi/abs/10.1002/dac.3706;2020;LSTM;False Positive Rate;OTROS;;;
S332 ; Deep Learning Inference at the Edge for Mobile and Aerial Robotics;10.1109/SSRR50563.2020.9292575;2475-8426;978-0-7381-1123-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9292575;2020;CNN;;OTROS;;;
S333 ; Deep Learning on Edge Device for Early Prescreening of Skin Cancers in Rural Communities;10.1109/GHTC46280.2020.9342911;2377-6919;978-1-7281-7388-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9342911;2020;CNN;Otro;;;;
S334 ; Deep Learning: Edge-Cloud Data Analytics for IoT;10.1109/CCECE.2019.8861806;2576-7046;978-1-7281-0319-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8861806;2019;DNN;;OTROS;;;
S335 ; Deep Learning-Based C/U Plane Separation Architecture for Automotive Edge Computing;10.1145/3318216.3363321;9.78E+12;;https://doi.org/10.1145/3318216.3363321;2019;CNN, FL;Accuracy;CIFAR-10;;;
S336 ; Deep Learning-Based Multiple Object Visual Tracking on Embedded System for IoT and Mobile Edge Computing Applications;10.1109/JIOT.2019.2902141;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8653851;2019;CNN;;OTROS;;;
S337 ; Deep Neural Network Based Computational Resource Allocation for Mobile Edge Computing;10.1109/GLOCOMW.2018.8644391;;978-1-5386-4920-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8644391;2018;AlexNet, LeNet, VGG;Loss Rate, Otro;OTROS;;;
S338 ; Deep Neural Network Compression Technique Towards Efficient Digital Signal Modulation Recognition in Edge Device;10.1109/ACCESS.2019.2913945;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8703045;2019;CNN;;CIFAR-10, MNIST, IMAGENET;;;
S339 ; Deep Neural Network Task Partitioning and Offloading for Mobile Edge Computing;10.1109/GLOBECOM38437.2019.9013404;2576-6813;978-1-7281-0962-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9013404;2019;MLP , SVM, DT, RF, LoR, KNN, NB;Accuracy, F-measure, Precision, Recall;OTROS;;Raspberry Pi;
S340 ; Deep PDS-Learning for Privacy-Aware Offloading in MEC-Enabled IoT;10.1109/JIOT.2018.2878718;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8515032;2019;QL ES RL;;;;;
S341 ; Deep Square Similarity Learning for Person Re-Identification in the Edge Computing System;10.1109/Cybermatics_2018.2018.00117;;978-1-5386-7975-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8726786;2018;CNN;Accuracy;OTROS;;;Wireless
S342 ; Deep Unified Model For Face Recognition Based on Convolution Neural Network and Edge Computing;10.1109/ACCESS.2019.2918275;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8721062;2019;SVM;ROC, Precision, Recall;OTROS;;;
S343 ; DeepCham: Collaborative Edge-Mediated Adaptive Deep Learning for Mobile Object Recognition;10.1109/SEC.2016.38;;978-1-5090-3322-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7774674;2016;DRL;Accuracy;CIFAR-10;;;
S344 ; Deep-Learning-Based Joint Resource Scheduling Algorithms for Hybrid MEC Networks;10.1109/JIOT.2019.2954503;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8907406;2020;DNN;;;;;
S345 ; DeepMDP: A Novel Deep-Learning-Based Missing Data Prediction Protocol for IoT;10.1109/JIOT.2020.3003922;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9121973;2021;YOLO, SVM, RF, KNN, NB;;;;;
S346 ; Deep-VFog: When Artificial Intelligence Meets Fog Computing in V2X;10.1109/JSYST.2020.3009998;1937-9234;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9171442;2020;DT;Accuracy, Precision, Recall;CIFAR-10;;;
S347 ; Dependent Task Offloading for Multiple Jobs in Edge Computing;10.1109/ICCCN49398.2020.9209593;2637-9430;978-1-7281-6607-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9209593;2020;CNN, ANN, SVM;Accuracy, Precision, Recall;CIFAR-10;;Otro;Wireless
S348 ; Deployment of Facial Recognition Models at the Edge: A Feasibility Study;10.23919/APNOMS50412.2020.9236972;2576-8565;978-89-950043-8-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9236972;2020;MLP ;Accuracy, Precision, Recall;CIFAR-10;;;
S349 ; Deployment of Object Detection Enhanced with Multi-label Multi-classification on Edge Device;10.1109/MWSCAS48704.2020.9184601;1558-3899;978-1-7281-8058-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9184601;2020;K-means;;;;;
S350 ; Design and Implementation of a Convolutional Neural Network on an Edge Computing Smartphone for Human Activity Recognition;10.1109/ACCESS.2019.2941836;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8839782;2019;VGG, ResNet;;;;Raspberry Pi;
S351 ; Design Flow of Accelerating Hybrid Extremely Low Bit-Width Neural Network in Embedded FPGA;10.1109/FPL.2018.00035;1946-1488;978-1-5386-8517-4;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8533487;2018;DQL, YOLO;;;;;Wireless, 4G/5G, Wi-Fi, Otro
S352 ; Detecting Advanced Persistent Threat in Edge Computing via Federated Learning;10.1007/978-981-15-9129-7_36;;;http://link.springer.com/chapter/10.1007/978-981-15-9129-7_36;2020;CNN, MLP ;Accuracy;CIFAR-10, MNIST;;Raspberry Pi, Jetson TX2, Otro;Wi-Fi
S353 ; Detecting Epileptic Seizures Using Deep Learning with Cloud and Fog Computing;10.1109/UCC-Companion.2018.00025;;978-1-7281-0359-4;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8605748;2018;YOLO;Accuracy;CIFAR-10;;;
S354 ; Detection and Recognition of Moving Biological Objects for Autonomous Vehicles Using Intelligent Edge Computing/LoRaWAN Mesh System;10.1007/978-3-030-65729-1_1;;;http://link.springer.com/chapter/10.1007/978-3-030-65729-1_1;2020;CNN;Accuracy, MAP, Precision;OTROS;;;
S355 ; Detection of Crossing Pedestrians and Control Support in Autonomous Vehicles using Edge-devices;10.1109/VNC48660.2019.9062791;2157-9865;978-1-7281-4571-6;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9062791;2019;DT;;;;Raspberry Pi;Wireless
S356 ; Development of Advanced Edge Computing Framework using Rich Client Devices;10.1109/ComNet47917.2020.9306109;2473-7585;978-1-7281-5320-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9306109;2020;BPNN;Accuracy;CIFAR-10;;Raspberry Pi;
S357 ; Distributed Active Learning Strategies on Edge Computing;10.1109/CSCloud/EdgeCom.2019.00029;;978-1-7281-1661-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8854053;2019;CNN, FL;Accuracy;CIFAR-10, MNIST;;;
S358 ; Distributed and Collaborative High Speed Inference Deep Learning for Mobile Edge with Topological Dependencies;10.1109/TCC.2020.2978846;2168-7161;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9036889;2020;LSTM, GRU;MAE, RMSE;;USB;Raspberry Pi;
S359 ; Distributed and Multi-Task Learning at the Edge for Energy Efficient Radio Access Networks;10.1109/ACCESS.2021.3050841;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9319651;2021;ANN, LSTM;MAE;;;;
S360 ; Distributed Deep Learning Model for Intelligent Video Surveillance Systems with Edge Computing;10.1109/TII.2019.2909473;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8681645;2019;AlexNet, LeNet, DENSENET, FL;Accuracy;CIFAR-10, MNIST, IMAGENET;;;
S361 ; Distributed Deep Learning-based Offloading for Mobile Edge Computing Networks;10.1007/s11036-018-1177-x;;;http://link.springer.com/article/10.1007/s11036-018-1177-x;2018;;Accuracy;OTROS;;;
S362 ; Distributed Deep Learning-based Task Offloading for UAV-enabled Mobile Edge Computing;10.1109/INFOCOMWKSHPS50562.2020.9162899;;978-1-7281-8695-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9162899;2020;TL;Accuracy;FRUIT;;Raspberry Pi;
S363 ; Distributed Deep Neural Network Deployment for Smart Devices from the Edge to the Cloud;10.1145/3331052.3332477;9.78E+12;;https://doi.org/10.1145/3331052.3332477;2019;LSTM;Accuracy;CIFAR-10;;;
S364 ; Distributed Deep Neural Network Training on Edge Devices;10.1145/3318216.3363324;9.78E+12;;https://doi.org/10.1145/3318216.3363324;2019;LeNet, VGG;Accuracy;OTROS;;;
S365 ; Distributed Fog Computing Architecture for Real-Time Anomaly Detection in Smart Meter Data;10.1109/BigDataService49289.2020.00009;;978-1-7281-7022-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9179551;2020;CNN, MobileNet, GOOGLE NET, SVM;False Negative Rate, False Positive Rate;OTROS;;Raspberry Pi;
S366 ; Distributed IoT Analytics across Edge, Fog and Cloud;10.1109/ICRCICN.2018.8718738;;978-1-5386-7638-7;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8718738;2018;DT, C4.5;Accuracy;CIFAR-10;;;Wireless, 4G/5G, Wi-Fi
S367 ; Distributed Machine Learning for Predictive Analytics in Mobile Edge Computing Based IoT Environments;10.1109/IJCNN48605.2020.9206867;2161-4407;978-1-7281-6926-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9206867;2020;SVM, J48, RF, KNN, NB;Accuracy;OTROS;;;
S368 ; Distributed Unsupervised Learning-Based Task Offloading for Mobile Edge Computing Systems;10.1007/978-3-030-67720-6_37;;;http://link.springer.com/chapter/10.1007/978-3-030-67720-6_37;2021;CNN, LSTM, FL;Otro;MNIST;;;
S369 ; DLASE: A light-weight framework supporting Deep Learning for Edge Devices;10.1109/SigTelCom49868.2020.9199058;;978-1-7281-6866-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9199058;2020;DENSENET, MobileNet, Inception, ResNet;Accuracy, F-measure;OTROS;;Raspberry Pi;
S370 ; Docker container based analytics at IoT edge Video analytics usecase;10.1109/IoT-SIU.2018.8519852;;978-1-5090-6785-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8519852;2018;SVM, DT, KNN, NB;Accuracy, F-measure, Precision, Recall;OTROS;;;
S371 ; Dynamic Collaboration of Centralized & Edge Processing for Coordinated Data Management in an IoT Paradigm;10.1109/AINA.2018.00105;2332-5658;978-1-5386-2195-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8432307;2018;FL;;;;;
S372 ; Dynamic Compression Ratio Selection for Edge Inference Systems With Hard Deadlines;10.1109/JIOT.2020.2997128;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9099284;2020;CNN, SVM, DT, RF, KNN;Accuracy, ROC, F-measure;CIFAR-10, MNIST, PASCAL;;;
S373 ; Dynamic resource allocation algorithm of virtual networks in edge computing networks;10.1007/s00779-019-01277-2;;;http://link.springer.com/article/10.1007/s00779-019-01277-2;2019;CNN;Cross Validation;OTROS;;;
S374 ; Dynamic Resource Allocation for Wireless Edge Machine Learning with Latency And Accuracy Guarantees;10.1109/ICASSP40776.2020.9052927;2379-190X;978-1-5090-6631-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9052927;2020;VGG;Otro;;;;
S375 ; Dynamically Growing Neural Network Architecture for Lifelong Deep Learning on the Edge;10.1109/FPL50879.2020.00051;1946-1488;978-1-7281-9902-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9221575;2020;MobileNet, ResNet;;CIFAR-10;;;
S376 ; EagleEYE: Aerial Edge-enabled Disaster Relief Response System;10.1109/EuCNC48522.2020.9200963;2575-4912;978-1-7281-4355-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9200963;2020;LSTM, RNN, LiR, LoR;;OTROS;;;
S377 ; EasiEdge: A Novel Global Deep Neural Networks Pruning Method for Efficient Edge Computing;10.1109/JIOT.2020.3034925;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9245564;2021;AlexNet, LeNet, MLP , RL;Errors;DIGITS;;;
S378 ; EDGE AI for Heterogeneous and Massive IoT Networks;10.1109/ICCT46805.2019.8947193;2576-7828;978-1-7281-0535-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8947193;2019;VGG, MobileNet, ResNet;Accuracy, Otro;CIFAR-10;;;
S379 ; Edge AI in Smart Farming IoT: CNNs at the Edge and Fog Computing with LoRa;10.1109/AFRICON46755.2019.9134049;2153-0033;978-1-7281-3289-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9134049;2019;DRL;;;;;
S380 ; Edge AI: On-Demand Accelerating Deep Neural Network Inference via Edge Computing;10.1109/TWC.2019.2946140;1558-2248;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8876870;2020;YOLO;Accuracy, F-measure, Precision, Recall;CIFAR-10, PASCAL;;Raspberry Pi;
S381 ; Edge AIBench: Towards Comprehensive End-to-End Edge Computing Benchmarking;10.1007/978-3-030-32813-9_3;;;http://link.springer.com/chapter/10.1007/978-3-030-32813-9_3;2019;DQN;;;;;
S382 ; Edge Computing Based Smart Aquaponics Monitoring System Using Deep Learning in IoT Environment;10.1109/SSCI47803.2020.9308395;;978-1-7281-2547-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9308395;2020;LSTM, RNN;;;;;4G/5G
S383 ; Edge Computing Based Traffic Analysis System Using Broad Learning;10.1007/978-3-030-22971-9_20;;;http://link.springer.com/chapter/10.1007/978-3-030-22971-9_20;2019;DRL;;;;;4G/5G
S384 ; Edge Computing for Having an Edge on Cancer Treatment: A Mobile App for Breast Image Analysis;10.1109/ICCWorkshops49005.2020.9145219;2474-9133;978-1-7281-7440-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9145219;2020;CNN, VGG;Accuracy, ROC, Precision, Recall;CIFAR-10, MNIST;;Raspberry Pi;
S385 ; Edge Computing for Road Safety Applications;10.1109/ICSEC47112.2019.8974789;;978-1-7281-2544-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8974789;2019;CNN;Accuracy;IMAGENET;;;
S386 ; Edge Computing Framework for Wearable Sensor-Based Human Activity Recognition;10.1007/978-3-030-24986-1_30;;;http://link.springer.com/chapter/10.1007/978-3-030-24986-1_30;2020;LSTM, RNN;MAPE, RMSE;;;;
S387 ; Edge Computing Resources Reservation in Vehicular Networks: A Meta-Learning Approach;10.1109/TVT.2020.2983445;1939-9359;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9051801;2020;RBF, SVM;Accuracy, Cross Validation;CIFAR-10, OTROS;;;
S388 ; Edge Computing System applying Integrated Object Recognition based on Deep Learning;10.23919/ICACT51234.2021.9370761;1738-9445;979-11-88428-06-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9370761;2021;MLP ;;;;Raspberry Pi;
S389 ; Edge Computing with Cloud for Voice Disorder Assessment and Treatment;10.1109/MCOM.2018.1700790;1558-1896;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8337897;2018;MLP , SVM, RF, KNN;Accuracy;DIGITS;;;
S390 ; Edge Computing-based 3D Pose Estimation and Calibration for Robot Arms;10.1109/CSCloud-EdgeCom49738.2020.00050;;978-1-7281-6550-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9170983;2020;DNN;;OTROS;;Raspberry Pi;
S391 ; Edge computing-based real-time passenger counting using a compact convolutional neural network;10.1007/s00521-018-3894-2;;;http://link.springer.com/article/10.1007/s00521-018-3894-2;2020;VGG;Accuracy, Sensitivity, Specificity;OTROS;;;
S392 ; Edge Computing-Enabled Deep Learning for Real-time Video Optimization in IIoT;10.1109/TII.2020.3020386;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9181434;2021;DENSENET, VGG, ResNet;Otro;IMAGENET;Batería;;
S393 ; Edge gradient feature and long distance dependency for image semantic segmentation;https://doi.org/10.1049/iet-cvi.2018.5035; ;;https://onlinelibrary.wiley.com/doi/abs/10.1049/iet-cvi.2018.5035;2019;DRL, DQL, DQN;;;;;
S394 ; Edge Inference for UWB Ranging Error Correction Using Autoencoders;10.1109/ACCESS.2020.3012822;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9151945;2020;YOLO;Otro;;;;Otro
S395 ; Edge Intelligence based Co-training of CNN;10.1109/ICCSE.2019.8845531;2473-9464;978-1-7281-1846-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8845531;2019;SVM;Accuracy;MNIST;;;Wireless
S396 ; Edge intelligence based Economic Dispatch for Virtual Power Plant in 5G Internet of Energy;https://doi.org/10.1016/j.comcom.2019.12.021;0140-3664;;https://www.sciencedirect.com/science/article/pii/S014036641931432X;2020;DML;;OTROS;;;Wireless
S397 ; Edge Intelligence for Real-Time Data Analytics in an IoT-Based Smart Metering System;10.1109/MNET.011.2000039;1558-156X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9199794;2020;MLP , SVM;Mean Squared Deviation;MNIST;Batería;;
S398 ; Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computing;10.1109/JPROC.2019.2918951;1558-2256;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8736011;2019;LSTM, DRL, DQL, DQN, FL;;;;;Wireless
S399 ; Edge pre-processing of traffic surveillance video for bandwidth and privacy optimization in smart cities;10.1109/BEC49624.2020.9276799;2382-820X;978-1-7281-9444-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9276799;2020;AlexNet, VGG, FCN/FRCNN, ERFNET, SegNet, ENET;;PASCAL;Batería;Otro;
S400 ; Edge-Based Discovery of Training Data for Machine Learning;10.1109/SEC.2018.00018;;978-1-5386-9445-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8567663;2018;DNN;Accuracy;MNIST;;Raspberry Pi;
S401 ; Edge-based street object detection;10.1109/UIC-ATC.2017.8397675;;978-1-5386-0435-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8397675;2017;CNN, MobileNet;Accuracy;CIFAR-10;;Raspberry Pi;
S402 ; Edge-Cloud Collaboration Architecture for AI Transformation of SME Manufacturing Enterprises;10.1109/AI4G50087.2020.9311075;;978-1-7281-7031-2;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9311075;2020;SVM;Detection Rate, F-measure, FAR, Mathew’s correlation coefficient, T racks;OTROS;;;
S403 ; EdgeCNN: A Hybrid Architecture for Agile Learning of Healthcare Data from IoT Devices;10.1109/PADSW.2018.8644604;1521-9097;978-1-5386-7308-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8644604;2018;YOLO;MAP, Recall;;;Jetson NX Xavier;
S404 ; Efficient Deep Structure Learning for Resource-Limited IoT Devices;10.1109/GLOBECOM42002.2020.9322206;2576-6813;978-1-7281-8298-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9322206;2020;DNN, CNN, SVM, RF;Accuracy, F-measure;OTROS;;;
S405 ; Embedded Deep Learning for Vehicular Edge Computing;10.1109/SEC.2018.00038;;978-1-5386-9445-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8567683;2018;CNN;Accuracy, F-measure;OTROS;;;
S406 ; Emotion Recognition for Cognitive Edge Computing Using Deep Learning;10.1109/JIOT.2021.3058587;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9352023;2021;CNN;;;;;
S407 ; Emotion recognition using secure edge and cloud computing;https://doi.org/10.1016/j.ins.2019.07.040;0020-0255;;https://www.sciencedirect.com/science/article/pii/S0020025519306486;2019;LSTM, SVR;MAE, R2, RMSE;OTROS;Solar;;
S408 ; Enabling High Availability Edge Computing Platform;10.1109/MobileCloud.2019.00019;2573-7562;978-1-7281-0463-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8710683;2019;ANN, SVM;Accuracy;OTROS;;;
S409 ; Energy Consumption Prediction System Based on Deep Learning with Edge Computing;10.1109/ELTECH.2019.8839589;;978-1-7281-1618-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8839589;2019;AlexNet, MobileNet, Inception, ResNet, GOOGLE NET;;;;;
S410 ; Enforcing Position-Based Confidentiality With Machine Learning Paradigm Through Mobile Edge Computing in Real-Time Industrial Informatics;10.1109/TII.2019.2898174;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8637769;2019;YOLO;Precision;PASCAL;;;
S411 ; Enhancing Performance of Gabriel Graph-Based Classifiers by a Hardware Co-Processor for Embedded System Applications;10.1109/TII.2020.2987329;1941-0050;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9072429;2021;ANN, LoR;Accuracy;CIFAR-10;;;
S412 ; Enhancing Sensing and Decision-Making of Automated Driving Systems With Multi-Access Edge Computing and Machine Learning;10.1109/MITS.2019.2953513;1941-1197;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9043489;2020;ANN, VGG;;;;;
S413 ; Exploring RRAM Variability as Synapses on Inception Simulation Framework to Characterize the Prediction Accuracy and Power Estimation per Bit for Convolution Neural Network;10.1109/IPFA49335.2020.9260780;1946-1550;978-1-7281-6169-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9260780;2020;DRL;;;;;
S414 ; Exploring the computational cost of machine learning at the edge for human-centric Internet of Things;https://doi.org/10.1016/j.future.2020.06.013;0167-739X;;https://www.sciencedirect.com/science/article/pii/S0167739X20304106;2020;DNN;Accuracy;CIFAR-10;;;
S415 ; Exploring the Power – Prediction Accuracy Trade-Off in a Deep Learning Neural Network using Wide Compliance RRAM Device;10.1109/ISNE.2019.8896449;2378-8607;978-1-7281-2062-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8896449;2019;CNN, SVM;Accuracy;MNIST, DIGITS;;Raspberry Pi;Wi-Fi
S416 ; FAST-RAM: A Fast AI-assistant Solution for Task Offloading and Resource Allocation in MEC;10.1109/GLOBECOM42002.2020.9322645;2576-6813;978-1-7281-8298-8;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9322645;2020;AlexNet, VGG;Accuracy;OTROS;Continua;Jetson TX2;Wireless
S417 ; Few-Shot Scale-Insensitive Object Detection for Edge Computing Platform;10.1109/TSUSC.2020.3043758;2377-3782;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9290143;2020;VGG, ResNet, GOOGLE NET;;;USB;;
S418 ; Flexible Low Power CNN Accelerator for Edge Computing with Weight Tuning;10.1109/A-SSCC47793.2019.9056941;;978-1-7281-5106-9;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9056941;2019;VGG, MobileNet, Inception;Accuracy, F-measure, Precision, Recall;CIFAR-10, PASCAL;;Raspberry Pi;Bluetooth
S419 ; FlowGuard: An Intelligent Edge Defense Mechanism Against IoT DDoS Attacks;10.1109/JIOT.2020.2993782;2327-4662;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9090824;2020;AlexNet;;;USB;Raspberry Pi;
S420 ; Fog Computing Approach for Music Cognition System Based on Machine Learning Algorithm;10.1109/TCSS.2018.2871694;2329-924X;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8488689;2018;;Accuracy;CIFAR-10;;;
S421 ; Fog computing based efficient IoT scheme for the Industry 4.0;10.1109/ECMSM.2017.7945879;;978-1-5090-5582-1;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7945879;2017;ANN;Accuracy;CIFAR-10;;;
S422 ; Fog Computing for Real-Time Accident Identification and Related Congestion Control;10.1109/SYSCON.2019.8836965;2472-9647;978-1-5386-8396-5;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8836965;2019;CNN, LSTM, MLP ;Accuracy, F-measure, Otro;OTROS;;Raspberry Pi, Jetson TX2;
S423 ; Fog Node Selection for Low Latency Communication and Anomaly Detection in Fog Networks;10.1109/CISCE.2019.00069;;978-1-7281-3681-3;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8805878;2019;YOLO;MAP;FRUIT;;Jetson TX2;
S424 ; Foothill: A Quasiconvex Regularization for Edge Computing of Deep Neural Networks;10.1007/978-3-030-27272-2_1;;;http://link.springer.com/chapter/10.1007/978-3-030-27272-2_1;2019;ANN, SVM, RF, LiR;MAE, RMSE;;;;
S425 ; Gait Recovery System for Parkinson’s Disease using Machine Learning on Embedded Platforms;10.1109/SysCon47679.2020.9275930;2472-9647;978-1-7281-5365-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9275930;2020;RF, KNN, NB;Accuracy, Sensitivity, Specificity;CIFAR-10;;Jetson Nano ;
S426 ; HealthDL'20: Proceedings of Deep Learning for Wellbeing Applications Leveraging Mobile Devices and Edge Computing;10.1109/ACCESS.2020.3039714;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9265295;2020;MLP ;Accuracy;OTROS;;Raspberry Pi;
S427 ; Hierarchical Ensemble Reduction and Learning for Resource-Constrained Computing;10.1145/3365224;1084-4309;;https://doi.org/10.1145/3365224;2019;MLP , SVM, DT, KNN, NB;Accuracy, F-measure, Precision, Recall;CIFAR-10, PASCAL;;;
S428 ; Home IoT Intrusion Prevention Strategy Based on Edge Computing;10.1109/ICECE48499.2019.9058536;;978-1-7281-4784-0;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9058536;2019;SVM;Accuracy;OTROS;;;
S429 ; Hybrid Deep Neural Networks for Friend Recommendations in Edge Computing Environment;10.1109/ACCESS.2019.2958599;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8930557;2020;MobileNet, YOLO, FL;Latency, MAP;COCO;Continua;Raspberry Pi;
S430 ; ICCF: An Information-Centric Collaborative Fog Platform for Building Energy Management Systems;10.1109/ACCESS.2019.2906645;2169-3536;;https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8672574;2019;;;OTROS;;;