Similarity: The Detection System of Helipad for Unmanned Aerial Vehicle Landing Using YOLO Algorithm

Suprapto, Bhakti Yudho (2022) Similarity: The Detection System of Helipad for Unmanned Aerial Vehicle Landing Using YOLO Algorithm. Turnitin Universitas sriwijaya, Universitas Ahmad Dahlan.

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Abstract

The challenge with using the Unmanned Aerial Vehicle (UAV) is when the UAV makes a landing. This problem can be overcome by developing a landing vision through helipad detection. This helipad detection can make it easier for UAVs to land accurately and precisely by detecting the helipad using a camera. Furthermore, image processing technology is used on the image produced by the camera. You Only Look Once (YOLO) is an image processing algorithm developed to detect objects in real-time. It results from the development of one of the Convolutional Neural Network (CNN) algorithm methods. Therefore, in this study, the YOLO method was used to detect a helipad in real-time. The models used in the YOLO algorithm were Mean-Shift and Tiny YOLO VOC. The Tiny YOLO VOC model performed better than the Mean-Shift method in detecting helipads. The test results obtained a confidence value of 91.1%, and the system processing speed reached 35 frames per second (fps) in bright conditions and 37 fps in dark conditions at an altitude of up to 20 meters.

Item Type:	Other
Subjects:	#3 Repository of Lecturer Academic Credit Systems (TPAK) > Results of Ithenticate Plagiarism and Similarity Checker
Divisions:	03-Faculty of Engineering > 20201-Electrical Engineering (S1)
Depositing User:	Mr. Bhakti Suprapto
Date Deposited:	18 Apr 2023 09:01
Last Modified:	18 Apr 2023 09:01
URI:	http://repository.unsri.ac.id/id/eprint/94803

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