Research Article
Enhancing Photovoltaic Module Fault Diagnosis with Unmanned Aerial Vehicles and Deep Learning-Based Image Analysis
Table 10
Training (a), validation (b), and test (c) accuracies of Bayes-based classifiers for various pretrained networks.
(a) Training accuracy of Bayes-based classifiers for various pretrained networks |
| Classifier | Training accuracy (%) | AlexNet | DenseNet-201 | GoogleNet | ResNet-50 | VGG16 | VGG19 |
| Bayes net | 96.38 | 96.58 | 93.25 | 96.15 | 92.18 | 94.04 | Naïve Bayes | 93.01 | 91.15 | 89.24 | 90.63 | 84.48 | 90.35 | Naïve Bayes multinomial text | 16.66 | 16.66 | 16.66 | 16.66 | 16.66 | 16.66 | Naïve Bayes updateable | 93.01 | 91.15 | 89.24 | 90.63 | 84.48 | 90.35 |
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(b) Validation accuracy of Bayes-based classifiers for various pretrained networks |
| Classifier | Validation accuracy (%) | AlexNet | DenseNet-201 | GoogleNet | ResNet-50 | VGG16 | VGG19 |
| Bayes net | 93.01 | 93.13 | 89.88 | 92.77 | 88.53 | 90.31 | Naïve Bayes | 92.50 | 91.15 | 88.49 | 90.07 | 83.92 | 89.80 | Naïve Bayes multinomial text | 16.66 | 16.66 | 16.66 | 16.66 | 16.66 | 16.66 | Naïve Bayes updateable | 92.50 | 91.15 | 88.49 | 90.07 | 83.92 | 89.80 |
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(c) Test accuracy of Bayes-based classifiers for various pretrained networks |
| Classifier | Test accuracy (%) | AlexNet | DenseNet-201 | GoogleNet | ResNet-50 | VGG16 | VGG19 |
| Bayes net | 94.60 | 94.13 | 89.33 | 93.65 | 87.30 | 89.84 | Naïve Bayes | 93.01 | 91.42 | 88.09 | 89.84 | 83.96 | 88.09 | Naïve Bayes multinomial text | 16.66 | 16.66 | 20.00 | 16.66 | 16.66 | 16.66 | Naïve Bayes updateable | 93.01 | 91.42 | 89.19 | 89.84 | 83.96 | 88.09 |
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Boldface entries represent the highest values obtained.
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