---
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}
}
```