太阳能电池图像数据集 - 资源下载

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太阳能电池图像数据集

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概述

内容: 该数据集包含2,624个300x300像素的8位功能和有缺陷太阳能电池的8位灰度图像样本，具有从44个不同太阳能模块中提取的不同程度的退化。带注释的图像中的缺陷是内部或外部类型的缺陷，已知会降低太阳能模块的功率效率。所有图像的大小和透视图均已标准化。另外，在提取太阳能电池之前，消除了由用于捕获EL图像的相机镜头引起的任何失真。可用于机器学习发现损坏的太阳能电池板的共同特征，帮助监控在使用的太阳能电池板是否存在问题。引用数据集时，请标注以下引用;

@InProceedings{Buerhop2018,
  author    = {Buerhop-Lutz, Claudia and Deitsch, Sergiu and Maier, Andreas and Gallwitz, Florian and Berger, Stephan and Doll, Bernd and Hauch, Jens and Camus, Christian and Brabec, Christoph J.},
  title     = {A Benchmark for Visual Identification of Defective Solar Cells in Electroluminescence Imagery},
  booktitle = {European PV Solar Energy Conference and Exhibition (EU PVSEC)},
  year      = {2018},
  eventdate = {2018-09-24/2018-09-28},
  venue     = {Brussels, Belgium},
  doi       = {10.4229/35thEUPVSEC20182018-5CV.3.15},
}

@TechReport{Deitsch2018,
  Title            = {Segmentation of Photovoltaic Module Cells in Electroluminescence Images},
  Author           = {Sergiu Deitsch and Claudia Buerhop-Lutz and Andreas K. Maier and Florian Gallwitz and Christian Riess},
  Year             = {2018},
  Archiveprefix    = {arXiv},
  Eprint           = {1806.06530},
  Journal          = {CoRR},
  Url              = {http://arxiv.org/abs/1806.06530},
  Volume           = {abs/1806.06530}
}

@Article{Deitsch2019,
  author    = {Sergiu Deitsch and Vincent Christlein and Stephan Berger and Claudia Buerhop-Lutz and Andreas Maier and Florian Gallwitz and Christian Riess},
  title     = {Automatic classification of defective photovoltaic module cells in electroluminescence images},
  journal   = {Solar Energy},
  year      = {2019},
  volume    = {185},
  pages     = {455--468},
  month     = jun,
  issn      = {0038-092X},
  doi       = {10.1016/j.solener.2019.02.067},
  publisher = {Elsevier {BV}},
}

转载：https://lme.tf.fau.de/person/deitsch/