Rice Plant Disease Detection Using AI | Web App for Real-Time Leaf Analysis with CNN

Rice Plant Disease Detection Using AI | Web App for Real-Time Leaf Analysis with CNN

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Learn how we built a Rice Plant Disease Detection Web App using Image Processing and Deep Learning (CNN). This project helps farmers detect leaf diseases like Brown Spot, Leaf Smut, and Bacterial Leaf Blight by simply uploading an image of the rice leaf.

In this project:

We trained a Convolutional Neural Network (CNN) to classify rice diseases

Used OpenCV for real-time detection

Developed a user-friendly AI-powered web interface

Enabled visual feedback for healthy vs infected leaves

This tool provides farmers and agricultural researchers with an automated and efficient solution to prevent crop losses and increase yield.

🔍 Key Features:

Multi-class classification (Brown Spot, Leaf Smut, Bacterial Leaf Blight)

Real-time detection using image upload

AI-powered web interface

High accuracy deep learning model

Built with Python, TensorFlow/Keras, and OpenCV

📂 Project Domain: Image Processing / Artificial Intelligence / Web App

🚀 Boost sustainable farming using AI!

🔗 Watch till the end to see the live demo!

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