Researching | Landing Runway Detection Algorithm Based on YOLOv5 Network Architecture

Laser & Optoelectronics Progress, Volume. 59, Issue 14, 1415017(2022)

Landing Runway Detection Algorithm Based on YOLOv5 Network Architecture

Ning Ma, Yunfeng Cao^*, Zhihui Wang, Xiangrui Weng, and Linbin Wu

Author Affiliations

College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu , China

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Figures&Tables (9)

References (15)

Paper Information

Figures & Tables(9)

Fig. 1. Framework of YOLOv5 network

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Fig. 2. Mosaic data augmentation method

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Fig. 3. Diagram of Focus module

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Fig. 4. Diagram of CSP module

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Fig. 5. Diagram of SPP module

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Fig. 6. Prediction mechanism introduced with runway image characteristics

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Fig. 7. Comparative experiment results for runway detection

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Fig. 8. Experiment results of runway corner prediction

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Table 1. Comparative analysis of performance of different runway detection algorithms
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Table 1. Comparative analysis of performance of different runway detection algorithms
method
Runway detection
AP /% Average speed /（frame·s^-1）
Scene 1 Scene 2 Scene 3 Scene 4 Scene 5
SR 0.95 0.76 0.78 0.52 0.81 0.1
Faster R-CNN 0.98 0.96 0.98 0.96 0.98 15
Proposed algorithm 0.99 0.99 0.99 0.99 0.99 125

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Ning Ma, Yunfeng Cao, Zhihui Wang, Xiangrui Weng, Linbin Wu. Landing Runway Detection Algorithm Based on YOLOv5 Network Architecture[J]. Laser & Optoelectronics Progress, 2022, 59(14): 1415017

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Paper Information

Category: Machine Vision

Received: Apr. 1, 2022

Accepted: May. 31, 2022

Published Online: Jul. 1, 2022

The Author Email: Yunfeng Cao (cyfac@nuaa.edu.cn)

DOI:10.3788/LOP202259.1415017

Topics

laser devices and laser physics

Lasers and Laser Optics

laser manufacturing

Instrumentation, Measurement and Metrology