At Awign, I perform image and video annotation according to project-specific guidelines. I review annotations for accuracy, consistency, and completeness, and correct errors based on the instructions provided.
For my AI Car project, I built a real-time road damage and lane detection system using YOLOv8 and OpenCV. It detected potholes, cracks, and lane markings with 92.5% accuracy at 20–30 FPS.
I also built a fertilizer planning system that uses soil data to recommend suitable plans. I applied K-Means to group soil datasets and the Firefly Optimization Algorithm to optimize recommendations.
I'm a B.Tech graduate in Artificial Intelligence and Machine Learning from Mohan Babu University. My technical skills include Python, Java, SQL, and supervised and unsupervised learning.
