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README.md
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| **Recall** | **83.8%** |
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| **Background Specificity** | **1.00 (Perfect)** |
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#### **
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*Figure 1: Normalized Confusion Matrix showing perfect separation of healthy tissue (Background).*
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*Figure 2: Precision-Recall curve confirming the 0.
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> **Note on Training Logs:** The `results.png` file reflects a high-intensity training run conducted without a validation split (`val=False`) to maximize the training data pool. Final metrics were verified using a separate hold-out test set as shown in the PR and F1 curves.
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| **Recall** | **83.8%** |
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| **Background Specificity** | **1.00 (Perfect)** |
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#### **Test Proof**
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*Figure 1: Normalized Confusion Matrix showing perfect separation of healthy tissue (Background).*
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*Figure 2: Precision-Recall curve confirming the 0.899 mAP score.*
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> **Note on Training Logs:** The `results.png` file reflects a high-intensity training run conducted without a validation split (`val=False`) to maximize the training data pool. Final metrics were verified using a separate hold-out test set as shown in the PR and F1 curves.
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