Plant Disease Detection

Summary

This repository contains a Convolutional Neural Network (CNN) model to detect and classify plant diseases from leaf images. This project was developed as part of CSC 542 - Neural Networks for the Spring 2024 semester, under the guidance of Dr. Edgar Lobaton at North Carolina State University (NCSU). Our project aims to automate plant disease detection and classification using CNNs, offering a faster and more accurate alternative to traditional methods that are labor-intensive and time-consuming.

Feature List

• CNN-based tool for early plant disease detection
• Helps farmers take timely interventions to prevent crop loss
• Improves crop management and food security
• Automates disease identification using deep learning
• Enhances agricultural productivity with AI-driven insights