Using segmentation-guided inpainting to remove co-occurring defects from electroluminescence images improves multi-label photovoltaic defect classification, with the largest gains on rare classes and low-data regimes.
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A Generative Approach for Improving Multi-Label Defect Classification in Photovoltaic Modules
Using segmentation-guided inpainting to remove co-occurring defects from electroluminescence images improves multi-label photovoltaic defect classification, with the largest gains on rare classes and low-data regimes.