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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.