Create README.md

README.md

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+pipeline_tag: image-classification
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+# Model Card: Fine-Tuned InceptionV3 & Xception for Human Decomposition Image Classification
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+These CNN models were developed for the classification of human decomposition images into various stage of decay categories, including fresh, early decay, 
+advanced decay, and skeletonized (Megyesi et al., 2005).
+
+## Model Details
+
+### Model Description
+
+- **Developed by:** Anna-Maria Nau
+- **Funded by:** National Institute of Justice
+- **Model type:** CNNs for Image Classification
+- **Base Model:** InceptionV3 and Xception pretrained on ImageNet
+- **Transfer Learning Method:** Two-step transfer learning: (1) freeze all pre-trained convolutional layers of the base model and train newly added classifier layers on custom dataset and (2) unfreeze all layers, and fine-tune model end-to-end on custom dataset.
+
+### Model Sources
+
+- **Paper :**
+  - [Stage of Decay Estimation Exploiting Exogenous and Endogenous Image Attributes to Minimize Manual Labeling Efforts and Maximize Classification Performance](https://ieeexplore.ieee.org/abstract/document/10222106)
+  - [Towards Automation of Human Stage of Decay Identification: An Artificial Intelligence Approach](https://arxiv.org/abs/2408.10414)
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+