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.
AI-Powered VGG16-based Method for Detecting, Classifying, and Visualizing Solar Panel Defects
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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.