Research for the Detection of Aircraft Target in Real-Time Based on YOLOv5
The rapid growth in civil aviation traffic and airport infrastructure has strained airport facilities, affecting safety and security. It is evident from the frequent displacement of aircraft. To ensure efficient airport operations and safety, developing and applying scientific and technological solu...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/adce/9521952 |
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| _version_ | 1849761109011070976 |
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| author | Bangjv Huang Bolin Ma Li Lu |
| author_facet | Bangjv Huang Bolin Ma Li Lu |
| author_sort | Bangjv Huang |
| collection | DOAJ |
| description | The rapid growth in civil aviation traffic and airport infrastructure has strained airport facilities, affecting safety and security. It is evident from the frequent displacement of aircraft. To ensure efficient airport operations and safety, developing and applying scientific and technological solutions that minimize accidents and improve space utilization and operational efficiency is crucial. This paper introduces an innovative real-time aircraft detection model based on YOLOv5, tailored for addressing aircraft scraping on airfields. We developed this model by collecting extensive operational imagery to create a comprehensive dataset and using it to build a detection system within the YOLOv5 framework. The model was tested through simulated operations on a physical airfield model, achieving an impressive average detection accuracy of 0.912. These results confirm the model’s effectiveness in real-world scenarios, significantly advancing precise aircraft detection. |
| format | Article |
| id | doaj-art-32ceb52463e341c7b75dad290e2a4d24 |
| institution | DOAJ |
| issn | 1687-8094 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-32ceb52463e341c7b75dad290e2a4d242025-08-20T03:06:09ZengWileyAdvances in Civil Engineering1687-80942025-01-01202510.1155/adce/9521952Research for the Detection of Aircraft Target in Real-Time Based on YOLOv5Bangjv Huang0Bolin Ma1Li Lu2School of Air Traffic ManagementSchool of Air Traffic ManagementSchool of Air Traffic ManagementThe rapid growth in civil aviation traffic and airport infrastructure has strained airport facilities, affecting safety and security. It is evident from the frequent displacement of aircraft. To ensure efficient airport operations and safety, developing and applying scientific and technological solutions that minimize accidents and improve space utilization and operational efficiency is crucial. This paper introduces an innovative real-time aircraft detection model based on YOLOv5, tailored for addressing aircraft scraping on airfields. We developed this model by collecting extensive operational imagery to create a comprehensive dataset and using it to build a detection system within the YOLOv5 framework. The model was tested through simulated operations on a physical airfield model, achieving an impressive average detection accuracy of 0.912. These results confirm the model’s effectiveness in real-world scenarios, significantly advancing precise aircraft detection.http://dx.doi.org/10.1155/adce/9521952 |
| spellingShingle | Bangjv Huang Bolin Ma Li Lu Research for the Detection of Aircraft Target in Real-Time Based on YOLOv5 Advances in Civil Engineering |
| title | Research for the Detection of Aircraft Target in Real-Time Based on YOLOv5 |
| title_full | Research for the Detection of Aircraft Target in Real-Time Based on YOLOv5 |
| title_fullStr | Research for the Detection of Aircraft Target in Real-Time Based on YOLOv5 |
| title_full_unstemmed | Research for the Detection of Aircraft Target in Real-Time Based on YOLOv5 |
| title_short | Research for the Detection of Aircraft Target in Real-Time Based on YOLOv5 |
| title_sort | research for the detection of aircraft target in real time based on yolov5 |
| url | http://dx.doi.org/10.1155/adce/9521952 |
| work_keys_str_mv | AT bangjvhuang researchforthedetectionofaircrafttargetinrealtimebasedonyolov5 AT bolinma researchforthedetectionofaircrafttargetinrealtimebasedonyolov5 AT lilu researchforthedetectionofaircrafttargetinrealtimebasedonyolov5 |