AI Data Annotation for Computer Vision Model Training
ImageBounding Box
Worked on a large-scale data annotation project for training computer vision models, handling over 50,000 real-world images. Performed precise bounding box annotations and image classification for objects like vehicles, pedestrians, and road signs, ensuring consistency across varying conditions such as lighting and occlusions. Followed strict annotation guidelines, conducted self and peer reviews, and maintained over 98% accuracy in QA audits. Collaborated with teams to refine labeling processes and improve dataset quality. Experienced with tools like LabelIing and CVAT, with strong attention to detail and efficiency in managing large datasets.
Worked on a large-scale data annotation project for training computer vision models, handling over 50,000 real-world images. Performed precise bounding box annotations and image classification for objects like vehicles, pedestrians, and road signs, ensuring consistency across varying conditions such as lighting and occlusions. Followed strict annotation guidelines, conducted self and peer reviews, and maintained over 98% accuracy in QA audits. Collaborated with teams to refine labeling processes and improve dataset quality. Experienced with tools like LabelIing and CVAT, with strong attention to detail and efficiency in managing large datasets.
2025 - 2025