AI Image Annotation for Autonomous Vehicle Object Detection
Worked on a large-scale computer vision project focused on training AI models for autonomous driving systems. My role involved annotating road images by drawing precise bounding boxes around objects such as vehicles, pedestrians, traffic signs, cyclists, and road obstacles. The project included over 25,000 images, requiring high accuracy and attention to detail. I followed strict annotation guidelines to ensure consistency across the dataset. Tasks included object classification, occlusion handling, and edge-case identification. Quality assurance measures included double-review processes, guideline compliance checks, and maintaining over 98% annotation accuracy. I collaborated with QA teams to correct errors and improve labeling standards.