Laser & Optoelectronics Progress, Volume. 56, Issue 7, 071001(2019)

Intelligent Target Recognition Method of Unmanned Aerial Vehicle Combat Platform

Panfei Lü* and Shuguang Wang
Author Affiliations
  • Army Artillery and Air Defense Forces Academy, Hefei, Anhui 230031, China
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    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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    Panfei Lü, Shuguang Wang. Intelligent Target Recognition Method of Unmanned Aerial Vehicle Combat Platform[J]. Laser & Optoelectronics Progress, 2019, 56(7): 071001

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    Paper Information

    Category: Image Processing

    Received: Sep. 17, 2018

    Accepted: Oct. 22, 2018

    Published Online: Jul. 30, 2019

    The Author Email: Lü Panfei (1055392772@qq.com)

    DOI:10.3788/LOP56.071001

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