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Laser & Optoelectronics Progress, Volume. 59, Issue 22, 2210012(2022)

Panicle Segmentation and Characteristics Analysis of Rice During Filling Stage Based on Neural Architecture Search

Jiawei Zhu1, Zhaohui Jiang1、*, Shilan Hong1, Huimin Ma1, Jianpeng Xu2, and Maosheng Jin3
Author Affiliations
  • 1School of Information and Computer Science, Anhui Agricultural University, Hefei 230036, Anhui, China
  • 2Anhui Province Rural Comprehensive Economic Information Center, Hefei 230036, Anhui, China
  • 3Agricultural Information Service Center of Quanjiao County Agricultural Committee, Chuzhou 239500, Anhui, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (17)
    Equations (11)
    References (22)
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    Paper Information
    Topics
    Figures & Tables(17)
    Panicle segmentation dataset

    Fig. 1. Panicle segmentation dataset

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    Overall flow of algorithm

    Fig. 2. Overall flow of algorithm

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    Schematic of different convolutions. (a) Normal convolution; (b) dilated convolution

    Fig. 3. Schematic of different convolutions. (a) Normal convolution; (b) dilated convolution

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    Structure of DeepLabV3Plus network[13]

    Fig. 4. Structure of DeepLabV3Plus network[13]

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    Schematic of DARTS[16]

    Fig. 5. Schematic of DARTS[16]

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    Modified ASPP

    Fig. 6. Modified ASPP

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    Curvature calculation

    Fig. 7. Curvature calculation

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    Segmentation results of three network models

    Fig. 8. Segmentation results of three network models

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    H channel first moment-second moment scatter diagram

    Fig. 9. H channel first moment-second moment scatter diagram

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    Contrast diagram of color feature of typical samples

    Fig. 10. Contrast diagram of color feature of typical samples

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    Area ratio - dispersion scatter diagram

    Fig. 11. Area ratio - dispersion scatter diagram

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    Contrast diagram of sparse and dense panicle of typical samples

    Fig. 12. Contrast diagram of sparse and dense panicle of typical samples

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    H channel first moment-mean curvature scatter diagram

    Fig. 13. H channel first moment-mean curvature scatter diagram

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    Contrast diagram of bending of panicle of typical samples

    Fig. 14. Contrast diagram of bending of panicle of typical samples

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    • Table 1. Distribution of panicle segmentation image dataset

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      Table 1. Distribution of panicle segmentation image dataset

      TrainTestSummary
      39398491

    • Table 2. Operating collection of search space

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      Table 2. Operating collection of search space

      No.OperationNo.Operation
      13×3 depthwise-separable Conv53×3 average pooling
      25×5 depthwise-separable Conv63×3 max pooling
      33×3 atrous Conv with dilation rate 27skip connection
      45×5 atrous Conv with dilation rate 28no connection（zero）

    • Table 3. Evaluation indexes for segmentation of three models

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      Table 3. Evaluation indexes for segmentation of three models

      MethodmIoU /%Acc /%Params size /MB
      DeepLabV3plus79.2489.64151.66
      NAS-DeepLab82.2091.3550.16
      Rice-DeepLab85.7492.6161.67
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    Jiawei Zhu, Zhaohui Jiang, Shilan Hong, Huimin Ma, Jianpeng Xu, Maosheng Jin. Panicle Segmentation and Characteristics Analysis of Rice During Filling Stage Based on Neural Architecture Search[J]. Laser & Optoelectronics Progress, 2022, 59(22): 2210012

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    Paper Information

    Category: Image Processing

    Received: Dec. 31, 2021

    Accepted: Mar. 30, 2022

    Published Online: Sep. 19, 2022

    The Author Email: Zhaohui Jiang (jiangzh@ahau.edu.cn)

    DOI:10.3788/LOP202259.2210012

    Topics

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