Update README.md

Corrected EfficientNet-B0 to EfficientNetV2-S

README.md

@@ -14,7 +14,7 @@ tags:
 
 # MedicalPatchNet: Model Weights
 
-This repository hosts the pre-trained model weights for **MedicalPatchNet** and the baseline **EfficientNet-B0** model, as described in our paper **MedicalPatchNet: A Patch-Based Self-Explainable AI Architecture for Chest X-ray Classification** [TODO ADD LINK].
+This repository hosts the pre-trained model weights for **MedicalPatchNet** and the baseline **EfficientNetV2-S** model, as described in our paper **MedicalPatchNet: A Patch-Based Self-Explainable AI Architecture for Chest X-ray Classification** [TODO ADD LINK].
 
 For the complete source code, documentation, and instructions on how to train and evaluate the models, please visit our main GitHub repository:
 
@@ -29,7 +29,7 @@ MedicalPatchNet is a self-explainable deep learning architecture designed for ch
 ### Key Features
 
 - **Self-explainable by design**: No need for external interpretation methods like Grad-CAM.
-- **Competitive performance**: Achieves comparable classification accuracy to a standard EfficientNet-B0.
+- **Competitive performance**: Achieves comparable classification accuracy to a standard EfficientNetV2-S.
 - **Superior localization**: Significantly outperforms Grad-CAM variants in pathology localization tasks.
 - **Faithful explanations**: Saliency maps directly reflect the model's true reasoning.
 
@@ -42,7 +42,7 @@ The weights provided here are intended to be used with the code from our [GitHub
 ## Models Included
 
 -   **MedicalPatchNet**: The main patch-based, self-explainable model.
--   **EfficientNet-B0**: The baseline model used for comparison with post-hoc methods (Grad-CAM, Grad-CAM++, and Eigen-CAM).
+-   **EfficientNetV2-S**: The baseline model used for comparison with post-hoc methods (Grad-CAM, Grad-CAM++, and Eigen-CAM).
 
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