Crop Disease Detection – Image Annotation Specialist
Performed polygon-based image annotation on crop photographs to support the development of an AI-powered disease detection model. Tasks included accurately labelling diseased regions on plant leaves, stems, and fruits across multiple crop types, while distinguishing between healthy and infected areas. Maintained high annotation quality by following detailed labeling guidelines, ensuring consistency across large image datasets, and adhering to quality control standards. Work directly contributed to training machine learning models capable of identifying and classifying crop diseases with greater precision.