AgroXG - Wheat Crop Disease Detection
This project can be divided into two parts:
- AI model training and selection: This work introduces a framework for solving a well-known problem included in Precision Agriculture known as the Disease Detection problem. Here, we majorly focus to detect the diseases of Wheat crop using pre-trained EfficientNetB0 as core model for transfer learning using heavily enhanced Gray-level Co-occurence Matrix (GLCM) as Input to the model.
- Deployment of the Web-App on kubenetes cluster: