Foyeke Oyediran

Key Skills

Software

HiveMind

OneForma

CVAT

Label Studio

Top Subject Matter

Street scene object detection

Customer review sentiment and intent classification

Named Entity Recognition of news articles

Top Data Types

Text

Image

Document

Top Task Types

Classification

Bounding Box

Segmentation

Question Answering

Text Summarization

Evaluation/Rating

Data Collection

Prompt + Response Writing (SFT)

Entity (NER) Classification

Polygon

Freelancer Overview

Object Detection Annotator – Street Scene Dataset (Personal Project). Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include CVAT and Label Studio. AI-training focus includes data types such as Image and Text and labeling workflows including Bounding Box, Classification, and Entity (NER) Classification.

Labeling Experience

Polygon & Semantic Segmenter – Agricultural Image Dataset (Personal Project)

CVATImagePolygon

Labeled agricultural drone images using polygon annotation and semantic segmentation techniques in CVAT. Delineated crop types, soil regions, and water bodies with precision, improving the accuracy of segmentation masks for model training. Compared annotations to ground truth samples for thorough quality assurance. • Applied polygon boundaries to irregular objects. • Used multi-label segmentation for diverse classes. • Carried out QA checks for annotation consistency. • Exported data for agricultural computer vision solutions.

Labeled agricultural drone images using polygon annotation and semantic segmentation techniques in CVAT. Delineated crop types, soil regions, and water bodies with precision, improving the accuracy of segmentation masks for model training. Compared annotations to ground truth samples for thorough quality assurance. • Applied polygon boundaries to irregular objects. • Used multi-label segmentation for diverse classes. • Carried out QA checks for annotation consistency. • Exported data for agricultural computer vision solutions.

2023 - 2023

Named Entity Recognition Annotator – News Article Dataset (Personal Project)

Label StudioTextEntity Ner Classification

Tagged named entities in 30+ news article excerpts using Label Studio, classifying persons, organizations, locations, dates, and products. Paid close attention to ambiguous abbreviations and overlapping entity spans to ensure precise labeling. Maintained inter-annotator consistency by flagging unclear cases for review. • Used NER guidelines for robust tag application. • Escalated edge cases for consistency checks. • Focused on precise, accurate entity boundary assignment. • Output was curated for downstream NLP tasks.

Tagged named entities in 30+ news article excerpts using Label Studio, classifying persons, organizations, locations, dates, and products. Paid close attention to ambiguous abbreviations and overlapping entity spans to ensure precise labeling. Maintained inter-annotator consistency by flagging unclear cases for review. • Used NER guidelines for robust tag application. • Escalated edge cases for consistency checks. • Focused on precise, accurate entity boundary assignment. • Output was curated for downstream NLP tasks.

2023 - 2023

Object Detection Annotator – Street Scene Dataset (Personal Project)

CVATImageBounding Box

Annotated 50+ images from a street scene dataset using CVAT, drawing bounding boxes around pedestrians, vehicles, and traffic signs. Ensured consistency across frames and conducted thorough reviews of annotations for label quality. Exported the dataset in COCO JSON format for AI model training purposes. • Applied multi-class labels consistently across objects. • Maintained high standards for annotation quality control. • Used visual inspection for self-QA and correction. • Demonstrated ability to follow detailed annotation guidelines.

Annotated 50+ images from a street scene dataset using CVAT, drawing bounding boxes around pedestrians, vehicles, and traffic signs. Ensured consistency across frames and conducted thorough reviews of annotations for label quality. Exported the dataset in COCO JSON format for AI model training purposes. • Applied multi-class labels consistently across objects. • Maintained high standards for annotation quality control. • Used visual inspection for self-QA and correction. • Demonstrated ability to follow detailed annotation guidelines.

2023 - 2023

Student Research & Content Reviewer

Label StudioTextClassification

As a Student Research & Content Reviewer, I reviewed and categorized academic and technical texts as part of various research projects. I was responsible for tagging written content by topic, tone, and relevance, which facilitated downstream data analysis and AI-oriented tasks. My work included proofreading, cleaning, and comparing research documents to ensure the accuracy and consistency of labeled data. • Categorized and tagged written text according to guidelines. • Proofread and cleaned datasets to identify inconsistencies, duplicates, and errors. • Compared multiple written responses to identify the clearest and most accurate submissions. • Reviewed structured data tables and flagged anomalies for correction.

As a Student Research & Content Reviewer, I reviewed and categorized academic and technical texts as part of various research projects. I was responsible for tagging written content by topic, tone, and relevance, which facilitated downstream data analysis and AI-oriented tasks. My work included proofreading, cleaning, and comparing research documents to ensure the accuracy and consistency of labeled data. • Categorized and tagged written text according to guidelines. • Proofread and cleaned datasets to identify inconsistencies, duplicates, and errors. • Compared multiple written responses to identify the clearest and most accurate submissions. • Reviewed structured data tables and flagged anomalies for correction.

2023 - 2023

Education

Work History