Pedestrian fall detection based on AC-YOLOv5s-Reference-Cited by-同舟云学术

Pedestrian fall detection based on AC-YOLOv5s

Published:2022-10-03 Issue: Volume: Page:
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Container-title:2022 IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC )
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Author:

Shen Guoxin¹,Wei Ziqin²,Li Xuerong³,Wei Yi¹,Li Ke⁴

Affiliation:

1. School of Automation, Wuhan University of Technology,Wuhan,China

2. School of Electrical Engineering, Zhengzhou University,Zhengzhou,China

3. College of mechanical and electrical engineering, Shanghai Donghai Vocational and Technical College,Shanghai,China

4. School of Food Engineering, Qingdao Institute of Technology,Qingdao,China

Publisher

IEEE

Link

Reference18 articles.

1. Vehicle and pedestrian detection model YOLO-DNF for assisted driving [J/OL];xiu yi;Computer Engineering and Applications,2022

2. Multi-scale feature fusion for lightweight nighttime infrared pedestrian detection in real time [J/OL];zifen;Chin J Lasers,2022

3. Improved YOLOv5s algorithm for pedestrian target detection in subway scenes[J/OL];xiu zai;Advanced Optoelectronics and Lasers,2022

4. An improved YOLOv3 algorithm for occlusion-oriented pedestrian detection[J];xiang;Journal of Optics,2022

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