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CVAT
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VideoFootball Video Annotation Project. Core strengths include CVAT. Education includes Master of Science, University of Nairobi (2024) and Bachelor of Science, University of Oxford (2021). AI-training focus includes data types such as Video and Image and labeling workflows including Bounding Box, Tracking, and Classification.
Ai training and data notation, classification of dataset my task include clasfication, labeling and basic image annotation
I categorized images into predefined classes to support supervised machine learning applications. The labeling process followed strict criteria to maximize classification accuracy. Regular feedback cycles were incorporated to optimize annotation quality. • Assigned class labels to hundreds of images • Enhanced annotated dataset diversity • Used classification standards and documentation • Assisted in label verification and corrections
I performed frame-by-frame tracking of pedestrians in urban video footage for people detection research. Each individual was consistently labeled throughout the sequences to ensure data integrity. Systematic validation processes were used to catch and correct errors. • Conducted detailed tracking of pedestrian paths • Focused on crowded urban scenes • Collaborated on annotation best practices • Delivered data for pedestrian detection models
I labeled vehicles such as cars, buses, and motorcycles in street images for object detection training. Annotations adhered to labeling guidelines to support robust model development. Images were reviewed and refined to meet dataset requirements. • Annotated a diverse range of vehicles • Used bounding boxes for clear object demarcation • Conducted multiple rounds of quality assurance • Supported dataset curation for detection models
I annotated football match videos by labeling players and tracking ball movement across frames. Each object instance was carefully identified and tracked for use in computer vision model training. Quality assurance measures were applied to maintain high dataset standards. • Labeled all visible players per frame • Applied frame-to-frame tracking using bounding boxes • Ensured precise annotation to improve detection accuracy • Reviewed and corrected annotations for consistency
Master of Science, Data Science and Analytics
Bachelor of Science, Data Science and Analytics
Senior Data Analyst
Data Analyst
