Aim:
To develop an enhanced LULC classification system using ResNet50v2 for better accuracy and LIME for explainability, while minimizing computational resource requirements.
Aim:
To develop a lightweight and efficient detection model using YOLO-v8 for identifying wind turbine blade defects with improved accuracy and real-time performance.