Naveen Thakur

Key Skills

Software

CVAT

Dataloop

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Audio

Image

Top Label Types

Bounding Box

Polygon

Point Key Point

Polyline

Segmentation

Freelancer Overview

I am a detail-oriented Data Annotation Specialist with 3 years of hands-on experience working on image, text, and object annotation projects to support AI and machine learning initiatives. My background includes labeling and categorizing large structured and unstructured datasets with over 95% accuracy, conducting rigorous quality checks, and consistently meeting tight deadlines. I am skilled in using MS Excel and other basic computer applications for data management, and I excel at maintaining data quality while improving annotation efficiency. My experience spans both independent and team-based projects, where I have collaborated closely with internal teams to ensure project accuracy and timely delivery. I am passionate about contributing to high-quality AI training data, and I bring strong attention to detail, time management, and a commitment to excellence in every task.

Labeling Experience

Image And Lidar Annotation

CVATImageBounding BoxPolygon

Project: Autonomous Vehicles Data Annotation Worked on data annotation projects supporting the development of AI models for autonomous (self-driving) vehicles. Responsible for accurately labeling and categorizing large volumes of image and sensor data to improve object detection, lane detection, and traffic recognition systems. Key Responsibilities: Annotated road objects including vehicles, pedestrians, traffic signs, traffic lights, and lane markings. Performed bounding box, polygon, and semantic segmentation annotation. Labeled complex driving scenarios such as intersections, highways, and urban traffic conditions. Conducted quality assurance checks to maintain high annotation accuracy (95%+). Followed strict annotation guidelines to ensure consistency across datasets. Worked with annotation tools for 2D image and video frame labeling. Tools & Techniques Used: Bounding Box Annotation Polygon & Semantic Segmentation Frame-by-Frame Video Annotation Data Quality Review & V

Project: Autonomous Vehicles Data Annotation Worked on data annotation projects supporting the development of AI models for autonomous (self-driving) vehicles. Responsible for accurately labeling and categorizing large volumes of image and sensor data to improve object detection, lane detection, and traffic recognition systems. Key Responsibilities: Annotated road objects including vehicles, pedestrians, traffic signs, traffic lights, and lane markings. Performed bounding box, polygon, and semantic segmentation annotation. Labeled complex driving scenarios such as intersections, highways, and urban traffic conditions. Conducted quality assurance checks to maintain high annotation accuracy (95%+). Followed strict annotation guidelines to ensure consistency across datasets. Worked with annotation tools for 2D image and video frame labeling. Tools & Techniques Used: Bounding Box Annotation Polygon & Semantic Segmentation Frame-by-Frame Video Annotation Data Quality Review & V

2023 - 2025

Education

Work History