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http://dx.doi.org/10.7471/ikeee.2021.25.2.285

Deep Learning Based Tank Aiming line Alignment System  

Jeong, Gyu-Been (Dept. of Information and Communication Engineering, Changwon National University)
Park, Jae-Hyo (Army Consolidated Maintenance Depot)
Seok, Jong-Won (Dept. of Information and Communication Engineering, Changwon National University)
Publication Information
Journal of IKEEE / v.25, no.2, 2021 , pp. 285-290 More about this Journal
Abstract
The existing aiming inspection use foreign-made aiming inspection equipment. However, the quantity is insufficient and the difficult to maintain. So it takes a lot of time to inspect the target. This system can reduces the time of aiming inspection and be maintained and distributed smoothly because it is a domestic product. In this paper, we develop a system that can detect targets and monitor shooting results through a target detection deep learning model. The system is capable of real-time detection of targets and has significantly increased the identification rate through several preprocessing of distant targets. In addition, a graphical user interface is configured to facilitate user camera manipulation and storage and management of training result data. Therefore the system can replace the currently used aiming inspection equipment and non-fire training.
Keywords
Tank; Aiming Inspection; Deep Learning; Target Detection; Computer Vision;
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