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.
Ā Ā Ā Ā Ā To develop a robust and scalable fraud detection framework for Unified Payments Interface (UPI) transactions using advanced ensemble and boosting algorithms such as Random Forest, Extra Trees, Cat Boost, and Light GBM.
Ā Ā Ā Ā The project aims to design a lightweight, high-precision breast-mass detection framework using YOLOv11 that can accurately identify lesions in ultrasound images. It seeks to reduce false detections and enable real-time performance on medical imaging systems.
Ā Ā Ā Ā Ā To develop a lightweight, accurate, and efficient YOLO-based deep learning model for detecting and classifying pavement defects such as cracks and potholes in real time, optimized for deployment.