Academic Project
CropDoc - Crop Disease Detection with XAI
A computer vision project that pairs crop disease classification with an interface and explanations designed for non-expert users.
What I built
I developed a neural network model for detecting crop diseases and connected it to a front-end application. An explainability layer makes the model's reasoning visible, helping users understand why an image received a particular prediction.
Result
- Reached 97.7% classification accuracy.
- Combined model inference, user-facing results, and explainable AI in one workflow.