Image Annotation for Object Detection (Autonomous Driving Dataset)
Completed a paid freelance data annotation project via platforms such as Remotasks and OpenTrain AI, focusing on labeling street-scene images for autonomous driving models. Annotated objects including vehicles, pedestrians, traffic signals, and road elements using bounding boxes and polygon tools in CVAT. Handled a dataset of ~8,000 images with a strong focus on accuracy, consistency, and edge-case handling (e.g., occlusions, truncation, low-light conditions). Regularly performed self-QA and incorporated reviewer feedback to improve labeling quality. Maintained high acceptance rates and consistently met turnaround time expectations.