Multimodal Data Labeling for AI Model Training
Participated in an image annotation project to support AI development in veterinary diagnostics. The task involved labeling microscopic images of cat and dog urine samples to identify and classify elements such as crystals, cells, and other particulates using bounding boxes. Ensured high accuracy by following veterinary imaging standards and performing QA reviews on labeled data. The annotated dataset was used to train models that assist in the early detection of urinary tract issues in pets.