Plant Disease Detection Using CNN | Deep Learning Project
Автор: Salon Rai
Загружено: 2025-04-02
Просмотров: 187
Описание:
This project implements a Convolutional Neural Network (CNN) to classify plant diseases in corn, potato, and tomato plants using deep learning.
🚀 Project Highlights:
✅ Dataset includes images of Common Rust (Corn), Early Blight (Potato), and Bacterial Spot (Tomato)
✅ CNN model built with Keras for high-accuracy image classification
✅ Optimized training pipeline: Data augmentation, normalization, and one-hot encoding
✅ Trained for 50 epochs with Adam optimizer and categorical crossentropy loss
✅ Model evaluation: Classification report, confusion matrix, and ROC AUC score
📊 The model was trained and tested on structured data, achieving high accuracy in detecting plant diseases.
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