Survey and Comparative Study for Drone Detection Using Deep Learning
Yazarlar (2)
Dr. Öğr. Üyesi Ziya TAN
Erzincan Binali Yıldırım Üniversitesi, Türkiye
Fırat Üniversitesi, Türkiye
| Bildiri Türü | Tebliğ/Bildiri |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) |
| Bildiri Niteliği | Alanında Hakemli Uluslararası Kongre/Sempozyum |
| Bildiri Dili | İngilizce |
| Kongre Adı | International Conference on Data Analytics for Business and Industry - ICDABI (DATA 2022) |
| Kongre Tarihi | 25-10-2022 / 26-10-2022 |
| Basıldığı Ülke | Bahreyn |
| Basıldığı Şehir | |
| Bildiri Linki | https://data.uob.edu.bh/ |
| Özet |
| The widespread use of drones and the reduction of costs have made studies with drones popular. Especially the studies using artificial intelligence are followed carefully. The increase in these studies has paved the way for the integration of artificial intelligence algorithms such as computer vision, object tracking, and object detection into drones to perform more complex tasks autonomously. In addition, unmanned aerial vehicles are used in many useful tasks to eliminate illegal security threats such as border violations and drug trafficking. For this reason, the importance of drones is increasing day by day. In this article, the articles related to drone detection using state-of-art deep learning algorithms in the last 3 years have been reviewed and compiled. In particular, the methods used, suggested approaches, analysis methods, and the results obtained in these articles are summarized. In terms of the algorithms used … |
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