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---
datasets:
- realslimman/REFUGE-MultiRater
library_name: keras
---
# Glaucoma Classifier
Model for detecting Glaucoma from retinal fundus images.
Trained as part of the paper: [Automated and Explainable Detection of Multiple
Diseases from Retinal Fundus Images](https://doi.org/10.1007/978-3-032-01169-5_9)
## Loading any one model
```python
from keras.models import model_from_json
import json
model = keras.Model.from_config(config)
model.load_weights("model.weights.h5")
with open("feature_based/CNN_ODOC/CNN_ODOC.json", 'r') as json_file:
model_json = json_file.read()
model = model_from_json(model_json)
model.load_weights("feature_based/CNN_ODOC/CNN_ODOC.weights.h5")
model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
```
## Performance
- Accuracy: **97.38%**
- Precision: **97.42%**
- Recall: **97.38%**
## Citation
```bibtex
@inproceedings{masti2026automated,
title={Automated and Explainable Detection of Multiple Diseases from Retinal Fundus Images},
author={Masti, Shubha and Prasad, T. and Srinivasa, G.},
booktitle={Image Processing and Vision Engineering. IMPROVE 2025},
series={Communications in Computer and Information Science},
volume={2628},
publisher={Springer},
year={2026},
doi={10.1007/978-3-032-01169-5_9}
}
```