Laser & Optoelectronics Progress, Volume. 59, Issue 16, 1615009(2022)

Shadow Detection Method for CRC-RetinaNet Photovoltaic Panel Based on Multiscale Fusion

Jun Wu, Penghui Fan, and Manli Wang*
Author Affiliations
  • School of Physics & Electronic Information Engineering, Henan Polytechnic University, Jiaozuo 454003, Henan , China
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    Figures & Tables(10)
    Structure of CRC-RetinaNet. (a) CSP backbone; (b) recursive-FPN; (c) class+box subnet
    Schematic of CSP DenseNet
    Cluster results of photovoltaic panel shadow dataset
    Training loss decline curve
    P-R curves of CRC-RetinaNet algorithm. (a) Photovoltaic panel; (b) photovoltaic panel shielding
    Detection results。(a) (b) (c) (d) (e) Dense and overlapping targets; (d) (e) small targets
    • Table 1. Confusion matrix of classification results

      View table

      Table 1. Confusion matrix of classification results

      Ground truthDetection result
      PositiveNegative
      PositiveTPFN
      NegativeFPTN
    • Table 2. Dataset distribution

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      Table 2. Dataset distribution

      ClassNumber of training set and verification setNumber of test set
      PVP462036017
      PVP_shielding462205049
    • Table 3. Performance comparison of different algorithms

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      Table 3. Performance comparison of different algorithms

      Algorithms

      AP /%

      mAP /%

      FPS

      Model size /MB

      PVP

      PVP_shielding

      M2Det

      96.89

      90.21

      93.55

      24.8

      226.66

      EfficientDet

      86.29

      39.09

      62.69

      30.7

      16.16

      SSD

      55.07

      30.55

      42.81

      41.4

      100.40

      SSD-anchor

      63.23

      52.15

      57.69

      42.3

      100.40

      Faster R-CNN

      40.66

      20.44

      30.55

      16.0

      301.05

      Faster R-CNN-anchor

      97.68

      94.42

      96.05

      18.5

      301.05

      YOLOv3

      95.81

      98.33

      97.07

      34.9

      246.30

      YOLOv4

      96.12

      98.09

      97.10

      30.2

      266.30

      RetinaNet

      96.92

      93.52

      95.22

      15.6

      139.30

      CRC-RetinaNet

      99.33

      99.15

      99.24

      32.4

      66.26

    • Table 4. Comparison of detection accuracy of different models

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      Table 4. Comparison of detection accuracy of different models

      GroupCSPRFPNMish +Leaky ReLUCIoU lossAP /%mAP /%FPSModel size /MB
      PVPPVP_shielding
      1××××96.9293.5295.2215.6139.30
      2×××98.2997.1297.7133.545.98
      3××98.9298.1798.5532.166.26
      4×99.0698.8898.9731.666.26
      599.3399.1599.2432.466.26
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    Jun Wu, Penghui Fan, Manli Wang. Shadow Detection Method for CRC-RetinaNet Photovoltaic Panel Based on Multiscale Fusion[J]. Laser & Optoelectronics Progress, 2022, 59(16): 1615009

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    Paper Information

    Category: Machine Vision

    Received: Jul. 30, 2021

    Accepted: Sep. 24, 2021

    Published Online: Jul. 22, 2022

    The Author Email: Manli Wang (wml920@163.com)

    DOI:10.3788/LOP202259.1615009

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