A hybrid feature extraction system using DenseNet-169 plus Gabor filters with an SVM classifier reaches 99.17% accuracy on augmented solar panel defect data.
Prominent solution for solar panel defect detection using AI-based computer vision technology with IoT sensors in the solar panel manufacturing industry
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Towards Automated Solar Panel Integrity: Hybrid Deep Feature Extraction for Advanced Surface Defect Identification
A hybrid feature extraction system using DenseNet-169 plus Gabor filters with an SVM classifier reaches 99.17% accuracy on augmented solar panel defect data.