Laser & Optoelectronics Progress, Volume. 58, Issue 8, 0810003(2021)

Yolo-C: One-Stage Network for Prohibited Items Detection Within X-Ray Images

Shouxiang Guo and Liang Zhang*
Author Affiliations
  • Tianjin Key Laboratory of Advanced Signal & Image Processing, Civil Aviation University of China, Tianjin 300300, China
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    Figures & Tables(13)
    Yolov3 network structure
    Composite backbone network structure
    Feature augment block
    Yolo-C network structure of one-stage dual-network object detection algorithm
    Random X-ray images of GDXray dataset
    Random X-ray images of SIXray dataset
    Sample display of prohibited items
    Comparison graph of network training process
    IoU definition and calculation diagram
    Detection results of experiments 3, 5 and 7
    • Table 1. Parameters of Yolo-C

      View table

      Table 1. Parameters of Yolo-C

      TypeLayerFilter numberSizeOutput
      DBLConv323×3416×416
      Res1Conv2643×3, 1×1208×208
      Upsample323×3416×416
      Res1'Conv2643×3, 1×1208×208
      Res2Conv41283×3, 1×1104×104
      Upsample643×3208×208
      Res2'Conv41283×3, 1×1104×104
      Res8Conv162563×3, 1×152×52
      Upsample1283×3104×104
      Res8'Conv162563×3, 1×152×52
      Res8Conv165123×3, 1×126×26
      Upsample2563×352×52
      Res8'Conv165123×3, 1×126×26
      Res4Conv810243×3, 1×113×13
      Upsample5123×326×26
      Res4'Conv810243×3, 1×113×13
      DBLConv303×313×13
      Head
      FABUpsample3×3, 1×126×26
      DBLConv303×326×26
      Head
      FABUpsample3×3, 1×152×52
      DBLConv303×352×52
      Head
    • Table 2. Analysis of different network complexity

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      Table 2. Analysis of different network complexity

      ModelBackboneFABFLOPsParams/106
      Yolov3DarkNet-5332.7761.55
      OursDarkNet-5335.5864.65
      DarkNet-C61.85105.93
    • Table 3. Ablation experiments on the Yolo-C network based on SIXray_OD dataset

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      Table 3. Ablation experiments on the Yolo-C network based on SIXray_OD dataset

      No.ModelBackboneFABAP for gun /%AP for knife /%AP for pliers /%AP for wrench /%AP for scissor /%mAP /%Detection rate /(frame·s-1)
      1SSDResNet5085.6972.4451.2160.6241.9962.3956
      2FASFResNet10182.7770.2348.657.738.759.648
      3Yolov3DarkNet-5388.6776.5352.4961.4142.664.3457
      4Faster-RCNNResNet10193.8383.7458.8571.5854.172.1810
      5OursDarkNet-5390.179.5755.6764.8151.0068.2355
      6DarkNet-C91.682.158.769.754.471.1042
      7DarkNet-C93.1483.1260.1873.8258.1473.6840
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    Shouxiang Guo, Liang Zhang. Yolo-C: One-Stage Network for Prohibited Items Detection Within X-Ray Images[J]. Laser & Optoelectronics Progress, 2021, 58(8): 0810003

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    Paper Information

    Category: Image Processing

    Received: Aug. 17, 2020

    Accepted: Sep. 9, 2020

    Published Online: Apr. 12, 2021

    The Author Email: Liang Zhang (l-zhang@cauc.edu.cn)

    DOI:10.3788/LOP202158.0810003

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