Edge device

A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art

Quoc‐Viet Pham, Fang Fang, Vu Nguyen Ha, Md. Jalil Piran, Mai Le, Long Bao Le, Won‐Joo Hwang, Zhiguo Ding

Citations: 846 • 2020

5G-Enabled Tactile Internet

Meryem Simsek, Adnan Aijaz, Mischa Döhler, Joachim Sachs, Gerhard Fettweis

Citations: 767 • 2016

A Survey on Federated Learning for Resource-Constrained IoT Devices

Ahmed Imteaj, Urmish Thakker, Shiqiang Wang, Jian Li, M. Hadi Amini

Citations: 719 • 2021

Deep learning models for cloud, edge, fog, and IoT computing paradigms: Survey, recent advances, and future directions

Shahnawaz Ahmad, Iman Shakeel, Shabana Mehfuz, Javed Ahmad

Citations: 177 • 2023

Multiagent Deep Reinforcement Learning for Joint Multichannel Access and Task Offloading of Mobile-Edge Computing in Industry 4.0

Zilong Cao, Pan Zhou, Ruixuan Li, Siqi Huang, Dapeng Wu

Citations: 176 • 2020

LiReD: A Light-Weight Real-Time Fault Detection System for Edge Computing Using LSTM Recurrent Neural Networks

Donghyun Park, Seulgi Kim, Yelin An, Jae‐Yoon Jung

Citations: 167 • 2018

Latent replay for real-time continual learning

Lorenzo Pellegrini, Gabriele Graffieti, Vincenzo Lomonaco, Davide Maltoni

Citations: 138 • 2020

AGLNet: Towards real-time semantic segmentation of self-driving images via attention-guided lightweight network

Quan Zhou, Yu Wang, Yawen Fan, Xiaofu Wu, Suofei Zhang, Bin Kang, Longin Jan Latecki

Citations: 129 • 2020

Characterizing the Deployment of Deep Neural Networks on Commercial Edge Devices

Ramyad Hadidi, Jiashen Cao, Yilun Xie, Bahar Asgari, Tushar Krishna, Hyesoon Kim

Citations: 109 • 2019

Real-time data reduction at the network edge of Internet-of-Things systems

Apostolos Papageorgiou, Bin Cheng, Ernő Kovács

Citations: 104 • 2015

Pruning deep convolutional neural networks for efficient edge computing in condition assessment of infrastructures

Rih‐Teng Wu, Ankush Singla, Mohammad R. Jahanshahi, Elisa Bertino, Bong Jun Ko, Dinesh Verma

Citations: 99 • 2019

Low-Power and High-Speed Deep FPGA Inference Engines for Weed Classification at the Edge

Corey Lammie, Alex Olsen, Tony Carrick, Mostafa Rahimi Azghadi

Citations: 98 • 2019

Deep Learning at the Mobile Edge: Opportunities for 5G Networks

Miranda McClellan, Cristina Cervelló-Pastor, Sebastià Sallent

Citations: 93 • 2020

Techology trend of edge AI

Yen-Lin Lee, Pei-Kuei Tsung, Max Wu

Citations: 86 • 2018

A Fog Robotics Approach to Deep Robot Learning: Application to Object Recognition and Grasp Planning in Surface Decluttering

Ajay Kumar Tanwani, Nitesh Mor, John Kubiatowicz, Joseph E. Gonzalez, Ken Goldberg

Citations: 81 • 2019

Accurate threat hunting in industrial internet of things edge devices

Abbas Yazdinejad, Behrouz Zolfaghari, Ali Dehghantanha, Hadis Karimipour, Gautam Srivastava, Reza M. Parizi

Citations: 79 • 2022

A Survey on the Optimization of Neural Network Accelerators for Micro-AI On-Device Inference

Arnab Neelim Mazumder, Jian Meng, Hasib-Al Rashid, Utteja Kallakuri, Xin Zhang, Jae-sun Seo, Tinoosh Mohsenin

Citations: 63 • 2021

STMTO: A smart and trust multi-UAV task offloading system

Jialin Guo, Guosheng Huang, Qiang Li, Naixue Xiong, Shaobo Zhang, Tian Wang

Citations: 62 • 2021

Enabling Edge-Cloud Video Analytics for Robotics Applications

Yiding Wang, Weiyan Wang, Duowen Liu, Xin Jin, Junchen Jiang, Kai Chen

Citations: 61 • 2022

EdgeDRNN: Recurrent Neural Network Accelerator for Edge Inference

Chang Gao, Antonio Ríos-Navarro, Xi Chen, Shih‐Chii Liu, Tobi Delbrück

Citations: 57 • 2020