Data Labelling
Project Scope: Contributed to an Automotive AI computer vision project focused on training autonomous driving systems to recognise and categorise various vehicles, pedestrians, and road hazards. Specific Tasks (i) Performed multi-class image classification on thousands of street-view images. (ii) Categorised objects based on precise criteria, i.e., distinguished between cyclists, sedans, SUVs, and stationary obstacles. (iii) Sorted and filtered low-quality and irrelevant images to maintain dataset integrity. Project Size: Handled a dataset of 200 images over one month. Quality Measures: Adhered to the strictly rigorous project-specific labelling guidelines, achieving a consistent accuracy verified through internal peer reviews and spot-checks.