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  • Published on  2022-01-25

    PEER Hub ImageNet (Φ-Net)-Detection Extention

    CSTR 31253.11.sciencedb.01472
    DOI 10.11922/sciencedb.01472

    Description

    This dataset is an extension of tasks 7 and 8 of the PEER Hub ImageNet (Φ-Net) classification dataset. The data provided here is annotated for the detection tasks in structural health monitoring. The dataset comprises two main related tasks (damage type and damage level) or sub-datasets. The damage type has four class instances: (1) Undamaged, (2) Flexural, (3) Shear, and (4) Combined Damage. The damage level also has four class instances: (1) Undamaged, (2) Minor, (3) Moderate, and (4) Heavy Damage.


    Further, data augmentation techniques including Mosiac, CutMix, and MixUp have been applied to increase the dataset size from 4585 to 11005 for the damage type and from 4636 to 10904 for the damage level.

    • Damage type
    • Damage level
    • Structural Health Monitoring
    • Civil Structures

    Subject:

      Civil and architectural engineeringEnvironmental science and resources science and technologyComputer science and technologyInformation and systems science related engineering and technology

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    Information

    • agyemangisaac45@gmail.com
    • 325.39 MB
    • 2
      • Version 1 published online
        2022-01-25 10:00:28 GMT+8

    Cite this Dataset

    Isaac Osei Agyemang. PEER Hub ImageNet (Φ-Net)-Detection Extention[DS/OL]. V1. Science Data Bank, 2022[2025-05-10]. https://cstr.cn/31253.11.sciencedb.01472. CSTR:31253.11.sciencedb.01472.
    Isaac Osei Agyemang. PEER Hub ImageNet (Φ-Net)-Detection Extention[DS/OL]. V1. Science Data Bank, 2022[2025-05-10]. https://doi.org/10.11922/sciencedb.01472. DOI:10.11922/sciencedb.01472.

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