A Drone Detection System for Preventing Security Threats Using YOLO Deep Learning Network

  • T. Kavitha, K. Lakshmi

Abstract

There has been a tremendous increase of use of UAVs or drones in the recent years. It is used in many fields such as aerial photography, shipping and delivery, crowd monitoring, crop monitoring in agriculture, law enforcement and surveillance etc. The cost of these devices become very low and makes it highly accessible to common public. It also increases the work efficiency and accuracy. Sometimes these drones are used for capturing information from secured areas by trespassing. This has raised several security concerns. In order to protect privacy and security at important locations, several solutions have been proposed in recent years. The drones are detected by using radio frequencies, acoustic waves, optic sensors and radars but they have certain limitations. Hence, this paper focuses on deep learning-based computer vision technique for detecting drones.

Published
2020-04-07
How to Cite
T. Kavitha, K. Lakshmi. (2020). A Drone Detection System for Preventing Security Threats Using YOLO Deep Learning Network. International Journal of Advanced Science and Technology, 29(5s), 1366 - 1376. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/8177