Gerald B.

Key Skills

Software

CVAT

Labelbox

LabelImg

Roboflow

Other

Top Subject Matter

Vehicles Domain Expertise

Traffic Systems

Urban Infrastructure

Top Data Types

Image

Text

Video

Top Task Types

Bounding Box

Segmentation

Classification

Object Detection

Entity (NER) Classification

Text Generation

Freelancer Overview

I am a Data Labeling and Image Annotation Specialist. With over 6 years of hands-on experience supporting AI and computer vision projects, I bring a strong track record of delivering precise, scalable, and high-quality annotated datasets that directly improve model performance. Throughout my freelance career, I have worked with startups, SMEs, and enterprise teams to annotate both small and large-scale datasets across diverse domains, including vehicles, traffic systems, urban infrastructure, human data, and natural environments. My expertise spans bounding box annotation, semantic and instance segmentation, and complex dataset structuring. I am highly proficient in tools such as CVAT, LabelMe, Labelbox, LabelImg, Roboflow, and various client-specific platforms, and I consistently deliver outputs in COCO, Pascal VOC, YOLO, JSON, and segmentation mask formats. What sets me apart is my commitment to accuracy, efficiency, and adaptability. I quickly align with project guidelines, maintain rigorous quality standards, and thrive in remote, cross-functional environments. I am passionate about contributing to the success of AI models by ensuring the data behind them is clean, consistent, and reliable.

Labeling Experience

Freelance Data Labeling Specialist

CVATImageBounding Box

As a Freelance Data Labeling Specialist, I provided high-quality annotations for computer vision and AI model training. I specialized in image annotation using bounding boxes, polygons, and segmentation for diverse industries and domains. My work consistently met strict quality control standards and enhanced the reliability of annotated datasets. • Annotated images of vehicles, traffic systems, urban infrastructure, humans, and natural environments. • Utilized CVAT, LabelMe, Labelbox, LabelImg, Roboflow, and client-specific annotation tools. • Delivered labeled datasets in COCO, Pascal VOC, YOLO, JSON, and segmentation mask formats. • Maintained accuracy, efficiency, and scalability across large, complex projects.

2020 - Present

Education

Work History