AI method grades solar panel defect severity from electroluminescence images
Researchers developed a self-supervised machine learning technique that automatically grades the severity of defects in photovoltaic panels using electroluminescence images. By using ordinal learning, the method ranks defect levels without needing large labeled datasets. This could improve quality control and maintenance in solar cell manufacturing.
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