Shahriya Rahman Shanto

Key Skills

Software

CVAT

Labelbox

Roboflow

Toloka

Top Subject Matter

No subject matter listed

Top Data Types

Document

Image

Text

Video

Top Label Types

Action Recognition

Bounding Box

Classification

Cuboid

Data Collection

Emotion Recognition

Entity Ner Classification

Land Cover Classification

Object Detection

Point Key Point

Polygon

Polyline

Segmentation

Tracking

Freelancer Overview

I am a detail-oriented AI Data Annotation Specialist with hands-on experience labeling and classifying visual data for machine learning models. My work includes image annotation using bounding boxes, classification, and tagging, always following strict guidelines to ensure high-quality, consistent results. I am skilled in using tools like CVAT and various web-based annotation platforms, and I adapt quickly to new technologies. My strengths include a strong focus on accuracy, attention to detail, and the ability to efficiently handle large datasets. I am reliable, deadline-driven, and passionate about supporting AI training workflows through precise and consistent data labeling.

Labeling Experience

Vehicle Detection

CVATImageBounding BoxPolygon

This project focused on annotating vehicle-related visual data to support the training and validation of computer vision models. The work involved labeling and reviewing images and videos of vehicles captured in diverse environments, lighting conditions, and traffic scenarios. Key tasks included bounding box annotation of vehicles (cars, Auto Taxi, motorcycles, ), classification of vehicle types, and tagging relevant attributes such as orientation, occlusion, truncation, and visibility. Additional annotations covered vehicle parts (wheels, headlights, mirrors), license plate regions, and motion direction where required by project guidelines.

This project focused on annotating vehicle-related visual data to support the training and validation of computer vision models. The work involved labeling and reviewing images and videos of vehicles captured in diverse environments, lighting conditions, and traffic scenarios. Key tasks included bounding box annotation of vehicles (cars, Auto Taxi, motorcycles, ), classification of vehicle types, and tagging relevant attributes such as orientation, occlusion, truncation, and visibility. Additional annotations covered vehicle parts (wheels, headlights, mirrors), license plate regions, and motion direction where required by project guidelines.

2025 - 2025

Education

Work History