Classification of Sugarcane Leaf Disease
Model Description
The model is based on EfficientNet architecture and has been fine-tuned on a balanced dataset containing six classes:
- Bacterial Blight Disease
- Healthy Leaves
- Mosaic Disease
- Red Rot Disease
- Rust Disease
- Yellow Disease
The model accepts RGB images of sugarcane leaves and outputs the predicted disease class.
Dataset
The dataset used for training consists of 19926 images of sugarcane leaves, evenly distributed across the six disease classes. Each image has been pre-processed and augmented to improve model performance.
Data Augmentation Techniques Used:
- Random rotation
- Flipping
- Zooming
- Resizing
- Cropping
Model Evaluation
Epoch [10/10], Loss: 0.2903, Accuracy: 90.28% Validation Loss: 0.3633, Accuracy: 86.32%
Accuracy_test: 0.8683
Acknowledgements
The dataset used for training can be found : https://www.kaggle.com/datasets/akilesh253/sugarcane-plant-diseases-dataset