ARTIFICIAL INTELLIGENCE BASED HELIPAD DETECTION WITH CONVOLUTIONAL NEURAL NETWORK
When a malfunction occurs in the helicopter or the pilot faints during a flight or performing a duty, and in order to ensure the safety of the pilot and the helicopter, a system must be available to detect the helicopter landing pads, so that the helicopter can land at the airport. Closest safe pla...
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| Format: | Article |
| Language: | English |
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Northern Technical University
2024-03-01
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| Series: | NTU Journal of Engineering and Technology |
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| Online Access: | https://journals.ntu.edu.iq/index.php/NTU-JET/article/view/799 |
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| _version_ | 1849225571323609088 |
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| author | Emad Ahmed Mohammed Ahmed J. Ali Abdullah Mohammed Abdullah |
| author_facet | Emad Ahmed Mohammed Ahmed J. Ali Abdullah Mohammed Abdullah |
| author_sort | Emad Ahmed Mohammed |
| collection | DOAJ |
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When a malfunction occurs in the helicopter or the pilot faints during a flight or performing a duty, and in order to ensure the safety of the pilot and the helicopter, a system must be available to detect the helicopter landing pads, so that the helicopter can land at the airport. Closest safe place immediately. This study focuses on helicopter landing pad detection using YOLOv8 and YOLOv5 models. A dataset of 1877 images collected from the Internet was used to evaluate the performance of the models. YOLOv8 showed good performance in helipad detection with 96.7% accuracy and 95.8% recall, resulting in an average accuracy (mAP@0.5) of 98.8%. As for YOLOv5, it reached 95.1% precision, 95.8% recall, and 97.5% mAP@0.5. Both models showed good results, but YOLOv8 outperformed it by a small percent.
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| format | Article |
| id | doaj-art-abe4a7b1422542f4879b021ccfca0d0d |
| institution | Kabale University |
| issn | 2788-9971 2788-998X |
| language | English |
| publishDate | 2024-03-01 |
| publisher | Northern Technical University |
| record_format | Article |
| series | NTU Journal of Engineering and Technology |
| spelling | doaj-art-abe4a7b1422542f4879b021ccfca0d0d2025-08-24T13:05:13ZengNorthern Technical UniversityNTU Journal of Engineering and Technology2788-99712788-998X2024-03-013110.56286/ntujet.v3i1.799800ARTIFICIAL INTELLIGENCE BASED HELIPAD DETECTION WITH CONVOLUTIONAL NEURAL NETWORKEmad Ahmed Mohammed0Ahmed J. Ali1Abdullah Mohammed Abdullah2Northern Technical UniversityNorthern Technical UniversityNorthern Technical University, Engineering Technical College of Mosul ,IRAQ When a malfunction occurs in the helicopter or the pilot faints during a flight or performing a duty, and in order to ensure the safety of the pilot and the helicopter, a system must be available to detect the helicopter landing pads, so that the helicopter can land at the airport. Closest safe place immediately. This study focuses on helicopter landing pad detection using YOLOv8 and YOLOv5 models. A dataset of 1877 images collected from the Internet was used to evaluate the performance of the models. YOLOv8 showed good performance in helipad detection with 96.7% accuracy and 95.8% recall, resulting in an average accuracy (mAP@0.5) of 98.8%. As for YOLOv5, it reached 95.1% precision, 95.8% recall, and 97.5% mAP@0.5. Both models showed good results, but YOLOv8 outperformed it by a small percent. https://journals.ntu.edu.iq/index.php/NTU-JET/article/view/799Helipad detection, YOLOv8, YOLOv5, Landing zone safety. |
| spellingShingle | Emad Ahmed Mohammed Ahmed J. Ali Abdullah Mohammed Abdullah ARTIFICIAL INTELLIGENCE BASED HELIPAD DETECTION WITH CONVOLUTIONAL NEURAL NETWORK NTU Journal of Engineering and Technology Helipad detection, YOLOv8, YOLOv5, Landing zone safety. |
| title | ARTIFICIAL INTELLIGENCE BASED HELIPAD DETECTION WITH CONVOLUTIONAL NEURAL NETWORK |
| title_full | ARTIFICIAL INTELLIGENCE BASED HELIPAD DETECTION WITH CONVOLUTIONAL NEURAL NETWORK |
| title_fullStr | ARTIFICIAL INTELLIGENCE BASED HELIPAD DETECTION WITH CONVOLUTIONAL NEURAL NETWORK |
| title_full_unstemmed | ARTIFICIAL INTELLIGENCE BASED HELIPAD DETECTION WITH CONVOLUTIONAL NEURAL NETWORK |
| title_short | ARTIFICIAL INTELLIGENCE BASED HELIPAD DETECTION WITH CONVOLUTIONAL NEURAL NETWORK |
| title_sort | artificial intelligence based helipad detection with convolutional neural network |
| topic | Helipad detection, YOLOv8, YOLOv5, Landing zone safety. |
| url | https://journals.ntu.edu.iq/index.php/NTU-JET/article/view/799 |
| work_keys_str_mv | AT emadahmedmohammed artificialintelligencebasedhelipaddetectionwithconvolutionalneuralnetwork AT ahmedjali artificialintelligencebasedhelipaddetectionwithconvolutionalneuralnetwork AT abdullahmohammedabdullah artificialintelligencebasedhelipaddetectionwithconvolutionalneuralnetwork |