A13019 - Livingstone-E LLM Project.
This project involves the construction and verification of a multi-modal (video-based) dataset.
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I am an experienced AI training specialist with a strong background in data annotation, image and video auditing, and audio transcription. I have contributed to multiple projects across platforms like CrowdGen, HiveWork, and Remotasks, working on computer vision tasks such as semantic segmentation, polylines, landmarks, bounding boxes, 3D cuboids, and LiDAR 3D maps. My work has also included translation, transcription, categorization, and sentiment analysis, giving me hands-on experience with both NLP and vision-based datasets. I am detail-oriented, skilled in time management, and thrive in collaborative environments, always focused on delivering high-quality labeled data to accelerate AI model development.
This project involves the construction and verification of a multi-modal (video-based) dataset.
The project focuses on transcribing audios, taking into consideration punctuation, filler & incomplete words and any background music or voices.
As a part of implementing a chess-playing robotic arm, we collected images of chess pieces, labeled and classified them (e.g. queen, king, knight etc..), then trained a yolo model to detect them.
Annotating and classifying different sections of documents.
The project focuses on drawing bounding boxes for couches, chairs, throw pillows, and tables in a presented image of indoor scene.
Bachelor of Science, Mechatronics Engineering
High School Diploma, Science, Technology, Engineering, and Mathematics
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