CottonLeafVision: An Explainable and Robust Deep Learning Framework for Cotton Leaf Disease Classification

1. 1Evaluate pre-trained Deep Convolutional Neural Networks such as DenseNet201, InceptionV3, and VGG19 for cotton leaf disease classification
2. 2Fine-tune the selected models using a cotton leaf disease dataset
3. 3Apply explainable AI techniques to interpret the classification results
4. 4Test the performance of the CottonLeafVision framework using metrics such as accuracy and F1-score
5. 5Deploy the framework in a real-world setting for cotton leaf disease detection and prevention

Data scientists and AI engineers on a team can benefit from CottonLeafVision to develop accurate disease classification models, while agronomists and farmers can use the framework for early disease detection and prevention

💡 Explainable AI can improve the accuracy and reliability of cotton leaf disease classification models, leading to better decision-making in agriculture

🌿💡 Classify cotton leaf diseases with CottonLeafVision, a robust deep learning framework for economic stability in the textile industry #AI #agriculture