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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    Figures & Tables(11)
    Diagram of YOLOv3 feature extraction and recognition
    Inception module
    Inception-ResNet module
    Diagram of darknet-139
    Curve of total loss
    Loss curve of 10000-50000 iterations
    Partial intermediate convolution results. (a) Layer 1; (b) layer 2; (c) layer 3; (d) layer 4; (e) layer 5; (f) layer 6; (g) layer 7; (h) layer 8; (i) original graph
    Target recognition effects. (a)(b) Tank target recognition; (c)(d) long-range rocket gun recognition; (e)-(h) antiaircraft gun recognition; (i) warship recognition
    Comparison of model recognition effect. (a)(b) YOLOv3; (c)(d) proposed model
    • Table 1. Comparison of computational complexity of different networks

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      Table 1. Comparison of computational complexity of different networks

      NetworkT(n)S(n)
      darknet-532.45×10104.05×107
      darknet-1392.69×10104.81×107
    • Table 2. Performance comparison of algorithms

      View table

      Table 2. Performance comparison of algorithms

      AlgorithmAP/%AP50/%Tm/ms
      YOLOv385.5087.4620
      Proposed87.5489.7325
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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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