A Reconfigurable Neural Architecture for Edge–Cloud Collaborative Real-Time Object Detection-Reference-Cited by-同舟云学术

A Reconfigurable Neural Architecture for Edge–Cloud Collaborative Real-Time Object Detection

Author:

Lee Joo Chan¹^ORCID,Kim Yongwoo²^ORCID,Moon Sungtae³,Ko Jong Hwan⁴^ORCID

Affiliation:

1. Department of Artificial Intelligence, Sungkyunkwan University, Suwon, South Korea

2. Department of System Semiconductor Engineering, Sangmyung University, Cheonan, South Korea

3. School of Computer Science and Engineering, Korea University of Technology and Education, Cheonan, South Korea

4. College of Information and Communication Engineering, Sungkyunkwan University, Suwon, South Korea

Funder

National Research Foundation of Korea

Institute of Information and Communications Technology Planning and Evaluation

Ministry of Science and ICT

Sungkyunkwan University and the BK21 FOUR

Ministry of Education

NRF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

Reference30 articles.

2. YOLOv4: Optimal speed and accuracy of object detection;bochkovskiy;arXiv 2004 10934,2020

5. Single-training collaborative object detectors adaptive to bandwidth and computation;assine;arXiv 2105 00591,2021

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