AI Trainer
Scope of the Project: The project focuses on supporting computer vision model development by reviewing and annotating large-scale image datasets. The goal is to ensure high-quality, accurately labeled visual data that can be used to train and improve AI systems. Specific Data Labeling Tasks Performed: I reviewed and labeled images based on detailed annotation guidelines, applying consistent tags, classifications, and attributes. I also identified edge cases, inconsistencies, and low-quality data, flagging or correcting them to improve overall dataset reliability. Project Size: The project involved handling a high volume of images on an ongoing basis, requiring sustained attention to detail and the ability to maintain accuracy across large datasets. Quality Measures Adhered To: Strict quality standards were followed, including adherence to project protocols, annotation guidelines, and regular quality checks. Accuracy, consistency, and guideline compliance were prioritized to ensure t