Justine Gumba

Key Skills

Software

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Image

Video

Top Label Types

Bounding Box

Polygon

Segmentation

Cuboid

Freelancer Overview

I have hands-on experience in data labeling and AI training data, particularly as a Super Reviewer and LiDAR annotator on the Remotask platform. My background includes working on various AI-related projects, where I was responsible for ensuring high-quality annotations and reviewing the work of others to maintain accuracy and consistency. I am highly organized, computer literate, and able to communicate effectively, which allows me to collaborate well with teams or work independently. My experience with administrative roles has also strengthened my attention to detail and ability to work efficiently under pressure. I am eager to contribute my skills in data annotation and quality assurance to support AI development projects.

Labeling Experience

Video Annotation 3D/2D

Scale AIVideoBounding BoxPolygon

Worked on annotating video data by labeling and tracking objects such as people, vehicles, and moving items across video frames in both 2D and 3D formats. Created bounding boxes, polygons, and 3D cuboids while following project guidelines to maintain accuracy and consistency. The annotated videos were used to train and improve AI models for computer vision applications like autonomous driving and video analysis.

Worked on annotating video data by labeling and tracking objects such as people, vehicles, and moving items across video frames in both 2D and 3D formats. Created bounding boxes, polygons, and 3D cuboids while following project guidelines to maintain accuracy and consistency. The annotated videos were used to train and improve AI models for computer vision applications like autonomous driving and video analysis.

2019

Image Labeling

Scale AIImageBounding Box

Worked on labeling images by identifying and tagging objects such as people, vehicles, and everyday items. Carefully followed labeling guidelines to ensure clear, accurate, and high-quality data used for training computer vision and AI models.

Worked on labeling images by identifying and tagging objects such as people, vehicles, and everyday items. Carefully followed labeling guidelines to ensure clear, accurate, and high-quality data used for training computer vision and AI models.

2019

Lidar Annotation

Scale AI3D SensorBounding Box

Worked on labeling 3D LiDAR data by marking objects such as cars, people, and road elements in point clouds. Followed project guidelines to ensure accurate and high-quality annotations used for training AI models.

Worked on labeling 3D LiDAR data by marking objects such as cars, people, and road elements in point clouds. Followed project guidelines to ensure accurate and high-quality annotations used for training AI models.

2019

Education

Work History