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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
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+These CNN models were developed for the classification of human decomposition images into six stages of human decay defined by Gelderman et al. (2018).
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+## Model Details
+
+### Model Description
+
+- **Developed by:** Anna-Maria Nau
+- **Funded by:** National Institute of Justice
+- **Model type:** CNNs for Image Classification
+- **Base Model:** InceptionV3, Xception, and ResNet50 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.
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+### 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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