Bell J.

Key Skills

Software

LabelImg

CVAT

Top Subject Matter

Artificial Intelligence

Object Detection

Classification Domain Expertise

Top Data Types

Image

Text

Document

Top Task Types

Bounding Box

Entity (NER) Classification

Classification

Freelancer Overview

Image & Text Data Annotation Project – Artificial Intelligence Course, UNN. Core strengths include LabelImg, CVAT, and Microsoft Excel. Education includes Bachelor of Science, University of Nigeria, Nsukka (2023) and Bachelor of Science, Middlesex University (2023). AI-training focus includes data types such as Image, Text, and Document and labeling workflows including Bounding Box, Entity (NER) Classification, and Classification.

Labeling Experience

Ongoing Data Annotation Tasks – Current Academic Work

LabelImgImageClassification

Actively contributes to ongoing labelling of structured and unstructured data as part of current academic work in AI and database projects. Handles labeling tasks across various data formats, focusing on both manual annotation and quality control. Engages in processes key to data preparation for AI model training and research. • Annotates images, text, and tabular data in academic projects. • Performs classification and verification of labeled data. • Utilizes institution-approved tools such as LabelImg and Excel for annotation. • Supports data preparation for AI coursework and research.

2024 - Present

Image & Text Data Annotation Project – Artificial Intelligence Course, UNN

LabelImgImageBounding Box

Performed manual and semi-automated labelling of image datasets for object detection and classification for an Artificial Intelligence course. Utilized labeling tools to annotate over 2,500 images with bounding boxes, segmentation masks, and object classes. Ensured data quality and consistency through adherence to strict annotation guidelines and review processes. • Annotated image datasets using LabelImg and CVAT. • Created bounding boxes, segmentation masks, and class categories. • Maintained accuracy and thoroughness in labelling process. • Focused on object detection and classification in the domain of AI coursework.

2023 - 2023

Sales & Customer Data Labelling & Cleaning – Business Intelligence Project, Middlesex University

TextEntity (NER) Classification

Labelled and categorized large sets of sales transaction and customer feedback data for business intelligence and machine learning projects. Performed data cleaning, sentiment labelling, and entity recognition to prepare structured datasets for further analytics. Improved dataset quality for analytical and predictive modeling purposes in an academic setting. • Categorized transactions and feedback via manual and semi-automated methods. • Applied sentiment labels and identified named entities in text. • Enhanced business intelligence datasets through quality control. • Used spreadsheet and data handling software in a business context.

2022 - 2023

Database-Driven Inventory Labelling System – Aptech Software Engineering Capstone

DocumentClassification

Designed and implemented a system to manage and label product inventory data as part of a capstone project. Developed automated categorization rules and conducted manual review to ensure high labeling accuracy. Achieved over 98% accuracy through a combination of SQL-based automation and manual validation. • Managed inventory data and performed data categorization using .NET and SQL Server. • Established and tested quality validation rules. • Labeled and maintained structured document data for inventory management. • Ensured accuracy and data integrity with QA checks.

2021 - 2021

Education

Work History