Intelligent Target Recognition Method of Unmanned Aerial Vehicle Combat Platform

被引：2
|
作者：
Lu Panfei [1 ]
Wang Shuguang [1 ]
机构：
[1] Army Artillery & Air Def Forces Acad, Hefei 230031, Anhui, Peoples R China
来源：
LASER & OPTOELECTRONICS PROGRESS | 2019年 / 56卷 / 07期
关键词：
image processing; unmanned aerial vehicle combat platform; artificial intelligence; target recognition;
D O I：
10.3788/LOP56.071001
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The popular target recognition method YOLOv3 is deeply studied, and the Inception module is integrated into the feature extraction network darknet-53 to get a new network darknet-139. Compared with YOLOv3, the new network has better ability in feature extraction. The data set required by the algorithm is collected and made, and were trained and tested on YOLOv3 and the proposed algorithm, respectively. The experimental results show that the average recognition rate of the proposed algorithm is about 2% higher than that of YOLOv3.
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页数：7
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