Research Article
Enhancing Photovoltaic Module Fault Diagnosis with Unmanned Aerial Vehicles and Deep Learning-Based Image Analysis
Table 11
Training (a), validation (b), and test (c) accuracies of lazy-based classifiers for various pretrained networks.
(a) Training accuracy of lazy-based classifiers for various pretrained networks |
| Classifier | Training accuracy (%) | AlexNet | DenseNet-201 | GoogleNet | ResNet-50 | VGG16 | VGG19 |
| IBK | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | K-star | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | 100.00 | LWL | 73.57 | 81.07 | 82.97 | 83.33 | 81.15 | 82.93 |
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(b) Validation accuracy of lazy-based classifiers for various pretrained networks |
| Classifier | Validation accuracy (%) | AlexNet | DenseNet-201 | GoogleNet | ResNet-50 | VGG16 | VGG19 |
| IBK | 99.24 | 99.84 | 99.44 | 99.68 | 99.20 | 99.28 | K-star | 99.24 | 99.64 | 99.13 | 99.48 | 98.96 | 98.80 | LWL | 73.17 | 80.31 | 16.66 | 82.57 | 79.92 | 82.34 |
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(c) Test accuracy of lazy-based classifiers for various pre-trained networks |
| Classifier | Test accuracy (%) | AlexNet | DenseNet-201 | GoogleNet | ResNet-50 | VGG16 | VGG19 |
| IBK | 99.84 | 100.00 | 99.80 | 99.68 | 99.52 | 99.84 | K-star | 99.52 | 100.00 | 99.04 | 99.52 | 99.52 | 99.36 | LWL | 76.03 | 80.00 | 82.85 | 82.22 | 77.77 | 80.63 |
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Boldface entries represent the highest values obtained.
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