Image Annotation and Quality Review for Industrial Dataset
I worked on a self-driven image annotation project focused on industrial and manufacturing datasets. The project involved labeling objects such as machinery, pipelines, and equipment using bounding box annotation techniques. I also reviewed auto-annotated images and corrected errors including missing labels and incorrect classifications to improve overall data quality. Through this project, I developed strong attention to detail and gained practical experience in maintaining annotation accuracy and consistency. I followed structured guidelines while working on multiple images and ensured that all annotations met quality standards. This experience helped me understand real-world AI training data workflows and improved my ability to efficiently review and correct large-scale datasets.