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}},
}
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