Abstract:
"The agricultural domain continually grapples with disease management, significantly impacting
yield and quality. This project addresses the challenge of early classification of banana leaf
diseases that is a critical issue for farmers in Sri Lanka where bananas are a staple crop. Traditional
methods of disease identification, reliant on visual inspection, suffer from issues of scale, accuracy,
and timeliness, leading to substantial crop losses.
To tackle this problem, the YellowB initiative leverages to create a robust Deep Learning (DL)
model through Transfer Learning (TL) techniques. This approach is complemented using
Explainable Artificial Intelligence (XAI) through Local Interpretable Model-agnostic
Explanations (LIME) to interpret model predictions, making the system's decisions transparent
and understandable to end-users."
