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README.md
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@@ -16,6 +16,8 @@ The solar-transformer model is designed to process EL images and predict the eff
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The solar-transformer model achieves state-of-the-art performance on the EL image dataset, with an accuracy of 91.7% on a classfication test. (defective or functional)
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ELPV-Monocystalline
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| Model | Recall | Precision | F1-Score |
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| Lumi-T | 0.9116 | 0.9509 | 0.9289 |
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| VGG-19 | 0.8462 | 0.8729 | 0.8462 |
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| ResNet-50 | 0.8269 | 0.8601 | 0.7951 |
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ELPV-Overall
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| Model | Recall | Precision | F1-Score |
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| VGG-19 | 0.8552 | 0.8552 | 0.7885 |
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| ResNet-50 | 0.8049 | 0.8476 | 0.8049 |
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ELPV-Transfer Learning (Monocrystalline to Polycrystalline)
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| Model | F1-Score |
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The solar-transformer model achieves state-of-the-art performance on the EL image dataset, with an accuracy of 91.7% on a classfication test. (defective or functional)
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ELPV dataset link:https://paperswithcode.com/dataset/elpv
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ELPV-Monocystalline
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| Model | Recall | Precision | F1-Score |
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|---|---|---|---|
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| Lumi-T | 0.9116 | 0.9509 | 0.9289 |
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| VGG-19 | 0.8462 | 0.8729 | 0.8462 |
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| ResNet-50 | 0.8269 | 0.8601 | 0.7951 |
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ELPV-Overall
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| Model | Recall | Precision | F1-Score |
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|---|---|---|---|
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| VGG-19 | 0.8552 | 0.8552 | 0.7885 |
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| ResNet-50 | 0.8049 | 0.8476 | 0.8049 |
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ELPV-Transfer Learning (Monocrystalline to Polycrystalline)
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| Model | F1-Score |
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