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Laser & Optoelectronics Progress, Volume. 62, Issue 2, 0215005(2025)

Electric Tricycle Detection Based on Improved YOLOv5s Model

Xiaofang Ou*, Fengchun Han, Jing Tian, Jijie Tang, and Zhengtao Yang
Author Affiliations
  • School of Traffic Management, People's Public Security University of China, Beijing 100038, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (14)
    Equations (7)
    References (23)
    Cited By (1)
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    Paper Information
    Topics
    Figures & Tables(14)
    YOLOv5s model structural diagram

    Fig. 1. YOLOv5s model structural diagram

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    Mosaic data augmentation

    Fig. 2. Mosaic data augmentation

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    SPPF module structure diagram

    Fig. 3. SPPF module structure diagram

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    PANet fusion structure diagram

    Fig. 4. PANet fusion structure diagram

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    Improved YOLOv5s structure diagram

    Fig. 5. Improved YOLOv5s structure diagram

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    CTR 3 encoder

    Fig. 6. CTR 3 encoder

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    Efficient additive attention mechanism

    Fig. 7. Efficient additive attention mechanism

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    Dataset images. (a) Crossroad; (b) T-shaped intersection; (c) main road; (d) expressway

    Fig. 8. Dataset images. (a) Crossroad; (b) T-shaped intersection; (c) main road; (d) expressway

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    Data enhanced images

    Fig. 9. Data enhanced images

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    Comparison chart between loss and mAP@0.5 change. (a) Loss; (b) mAP@0.5

    Fig. 10. Comparison chart between loss and mAP@0.5 change. (a) Loss; (b) mAP@0.5

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    FPS-mAP@0.5 coordinate diagram

    Fig. 11. FPS-mAP@0.5 coordinate diagram

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    Comparison of detection results diagram. (a) Original model; (b) proposed model

    Fig. 12. Comparison of detection results diagram. (a) Original model; (b) proposed model

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    • Table 1. Ablation experiments

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      Table 1. Ablation experiments

      ModulePrecision /%Recall /%mAP@0.5 /%FPSSize
      YOLOv5s90.5482.6784.686814.36
      YOLOv5s+New head89.8783.7986.97（+2.29）6615.75
      YOLOv5s+Transformer88.7483.5985.64（+0.96）7015.79
      YOLOv5s+EAA88.3183.2485.59（+0.91）9614.27
      YOLOv5s+New head+Transformer+EAA91.1584.8889.58（+4.90）9216.14

    • Table 2. Comparative experiment

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      Table 2. Comparative experiment

      ModelPrecision /%Recall /%mAP@0.5/%FPS /（frame/s）Size /Mbit
      SSD83.5682.3984.532856.74
      Faster-RCNN85.4983.4586.491341.87
      YOLOv3-tiny79.5868.7476.7212116.59
      YOLOv8s91.3285.7390.437421.44
      YOLOv5s90.5482.6784.686814.36
      Proposed91.1584.8889.589216.14
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    Xiaofang Ou, Fengchun Han, Jing Tian, Jijie Tang, Zhengtao Yang. Electric Tricycle Detection Based on Improved YOLOv5s Model[J]. Laser & Optoelectronics Progress, 2025, 62(2): 0215005

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    Paper Information

    Category: Machine Vision

    Received: Apr. 9, 2024

    Accepted: Jun. 3, 2024

    Published Online: Jan. 6, 2025

    The Author Email:

    DOI:10.3788/LOP241065

    CSTR:32186.14.LOP241065

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology