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app.py
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@@ -36,7 +36,7 @@ Siamo dei ricercatori del laboratorio [AImageLab](https://aimagelab.ing.unimore.
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Alcuni di noi lavorano sul **Medical Imaging con uso di Intelligenza Artificiale** π§ π§ββοΈπ©ββοΈπ₯Ό
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### Technical Details π€
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The architecture used is a pre- trained Vision Transformer (ViT) on the ImageNet21k, with a fine-tuning on the [HAM10k dataset](https://huggingface.co/datasets/marmal88/skin_cancer) and a modified head to accommodate for the classes:
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The best validation accuracy obtained was 0.9695. However this score is not a good indicator of performance given the class imbalances present in the dataset.
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### Credits
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Alcuni di noi lavorano sul **Medical Imaging con uso di Intelligenza Artificiale** π§ π§ββοΈπ©ββοΈπ₯Ό
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37 |
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### Technical Details π€
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The architecture used is a pre- trained Vision Transformer (ViT) on the ImageNet21k, with a fine-tuning on the [HAM10k dataset](https://huggingface.co/datasets/marmal88/skin_cancer) and a modified head to accommodate for the classes: Benign keratosis-like lesions, Basal cell carcinoma, Actinic keratoses, Vascular lesions, Melanocytic nevi, Melanoma, Dermatofibroma.
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The best validation accuracy obtained was 0.9695. However this score is not a good indicator of performance given the class imbalances present in the dataset.
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### Credits
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