Edge YOLO: Real-Time Intelligent Object Detection System Based on Edge-Cloud Cooperation in Autonomous Vehicles-Reference-Cited by-同舟云学术

Edge YOLO: Real-Time Intelligent Object Detection System Based on Edge-Cloud Cooperation in Autonomous Vehicles

Author:

Liang Siyuan¹,Wu Hao¹^ORCID,Zhen Li¹^ORCID,Hua Qiaozhi²^ORCID,Garg Sahil³^ORCID,Kaddoum Georges⁴^ORCID,Hassan Mohammad Mehedi⁵^ORCID,Yu Keping⁶^ORCID

Affiliation:

1. Shaanxi Key Laboratory of Information Communication Network and Security, Xi’an University of Posts and Telecommunications, Xi’an, China

2. Computer School, Hubei University of Arts and Science, Xiangyang, China

3. Resilient Machine Learning Institute (ReMI), École de Technologie Supérieure, Montréal, QC, Canada

4. Electrical Engineering Department, École de Technologie Supérieure, Montréal, QC, Canada

5. Department of Information Systems, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

6. Global Information and Telecommunication Institute, Waseda University, Tokyo, Japan

Funder

King Saud University, Riyadh, Saudi Arabia, through the Researchers Supporting Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

Reference49 articles.

4. MobileNets: Efficient convolutional neural networks for mobile vision applications;howard;arXiv 1704 04861,2017

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