GitHub - Prarabdha14/Cotton-disease-prediction-: This repository explores the prediction of cotton diseases using deep learning models with transfer learning. Two popular convolutional neural network architectures, InceptionV3 and ResNet50, are employed and fine-tuned on a dataset of cotton leaf images with disease labels.

Key Features:

Transfer Learning: Leverages pre-trained models (InceptionV3 and ResNet50) trained on ImageNet for efficient feature extraction.

Data Preprocessing: Includes image loading, resizing, augmentation (e.g., rotation, flipping, zooming), and data splitting.

Model Fine-tuning: Fine-tunes the pre-trained models on the cotton disease dataset by retraining the top layers.

Model Evaluation: Evaluates model performance using metrics such as accuracy, precision, recall, F1-score, and AUC-ROC.

Visualization: Visualizes model predictions and feature maps to gain insights into the model's decision-making process.

Name		Name	Last commit message	Last commit date
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README.md		README.md
Transfer Learning Inception V3.ipynb		Transfer Learning Inception V3.ipynb
Transfer Learning Resnet 50.ipynb		Transfer Learning Resnet 50.ipynb

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