Update README.md

README.md

@@ -46,7 +46,7 @@ model-index:
             name: TTA Accuracy
 ---
 
-![Arch-Building-Image-Classification](results/greyscope-labs-arch-building-classification-hunggingface-cnn-densenet121.png)
+![Arch-Building-Image-Classification](results/greyscope-labs-architecture-classification-cnn-transferlearning.PNG)
 
 # Fine-Grained Image Classification of World Architecture: A DenseNet121 Transfer Learning Approach with Layered Regularization
 
@@ -496,7 +496,6 @@ print(f"Predicted: {LABELS[np.argmax(preds)]} ({np.max(preds)*100:.1f}%)")
 - Trained on Pexels stock photography — performance may differ on user-generated or field photographs
 - Limited to 8 architectural classes (barn, bridge, castle, mosque, skyscraper, stadium, temple, windmill)
 - Confusion pair analysis found **0 significant pairs** (threshold >5%) — all 8 classes are well-distinguished by the model; see `confusion_pairs.json` for details
-- Barn and windmill share 3 cross-class duplicates (0.02% of dataset) — left as-is due to negligible impact
 - Inference confidence can be low on atypical examples
 
 ![Misclassification Examples](results/misclassification_examples.png)