Update README.md

README.md

@@ -15,24 +15,27 @@ This CNN model was developed to perform human bodypart classification.
 - **Model type:** CNNs for Image Classification
 - **Base Model:** InceptionV3 pretrained on ImageNet
 
+### Model Sources
+
+- **Paper :**
+  - [Collaborative Learning of Semi-Supervised Clustering and Classification for Labeling Uncurated Data](https://ieeexplore.ieee.org/abstract/document/10222106)
+
 ## Dataset
 
 - Dataset Name: Human Decomposition Image Dataset
 - Source: The dataset used in this study was obtained from the Forensic Anthropology Center (FAC) at the University of Tennessee, Knoxville, but due to privacy considerations, it is not available for public access. Please reach out to obtain access.
-- Classes: 'arm', 'hand', 'foot', 'legs','fullbody','head','backside', 'torso', 'stake', 'plastic'. 'stake' and 'plastic' classes were
+- Classes: arm, hand, foot, legs, fullbody, head, backside, torso, stake, and plastic. stake and plastic classes were
 included for filtering out images where bodyparts are covered with plastic or images showing stake with unanonymized donor IDs,
 which is often the case in forensic anthropology.
 
 ## Usage
-The stage of decay classification is bodypart specific (i.e., head, torso, or limbs), so make sure to pick the correct bodypart model.
-
 ```python
 from tensorflow.keras.models import load_model
 import numpy as np
 from tensorflow.keras.preprocessing.image import img_to_array, load_img
 
 # Load the entire model
-model = load_model('path_to_your_model')  # e.g. head/inceptionV3 to perform stage of decay classfication of head images
+model = load_model('inception_acc_0.989001-_val_acc_0.98252.h5')  
 
 # Load and preprocess an image
 img = load_img('path_to_image.jpg', target_size=(299, 299))  # adjust size as per model input