← Back to Projects
Machine Learning

Rice Leaf Disease Classification

Apr — May 2025

Overview

A deep learning model for classifying rice leaf diseases, trained on the Rice Leaf Diseases Dataset from Kaggle.

Background

This project explores how computer vision can help farmers identify common rice leaf diseases early from a photo, instead of waiting for visible crop damage.

Problem Statement

Rice leaf diseases are often noticed only after visible damage has spread, by which point yield loss is harder to prevent. Manual identification also requires expertise farmers may not have.

Objectives

  • Train a CNN model on the public Rice Leaf Diseases dataset.
  • Classify common disease types such as Bacterial Leaf Blight, Brown Spot, and Leaf Blast.
  • Evaluate the model as an academic machine learning exercise.