LeafGuard: An AI-Driven Approach for Early Detection of Plant Pathogen Infections

The development of an advanced machine learning model for plant disease detection using deep learning methods is the research objective. A plant pathogen image dataset from Kaggle will be used for proper classification of plant health based on various diseases, such as bacterial infection, fungi growth, pests, and viral diseases. Three deep learning models, namely CNN, ResNet, and MobileNet, will be trained on the dataset to make accurate plant health condition predictions. These models will classify plants according to health status and whether affected by bacteria, fungus, pests, virus, or are healthy. The proposed system will upload plant images, and the trained model will provide health predictions. This approach will serve as an effective tool for early detection, improving agricultural practices by enabling timely interventions.