Yuan Q.

Key Skills

Software

LabelImg

Data Annotation Tech

Top Subject Matter

AI model training

industrial object detection

Safety helmet detection in construction sites

Top Data Types

Image

Top Task Types

Bounding Box

Object Detection

Fine-tuning

Freelancer Overview

Large Model Algorithm Intern – Data Annotation & Training. Core strengths include LabelImg and Visionmaster. Education includes Bachelor of Science, 广州南方学院 (2026). AI-training focus includes data types such as Image and labeling workflows including Bounding Box and Object Detection.

Labeling Experience

Vision Lab Researcher – AI Training & Labeling

ImageObject Detection

I systematically applied industrial computer vision tools to develop data labeling pipelines for defect detection, color recognition, and feature extraction. Data annotation tasks involved configuring and tuning workflows in the Visionmaster software, handling real-world samples under diverse conditions. The experience incorporated hands-on integration of labeled visual data with both hardware and machine learning models. • Selected and configured cameras, lenses, and lighting for image data capture. • Designed object detection workflows and annotated images for multiple detection tasks. • Tuned annotation parameters for accuracy in different visual conditions. • Maintained and troubleshot data pipelines for ongoing AI visual projects.

2025 - Present

Data Annotation/AI Trainer – YOLOv8 Project

LabelImgImageFine-tuning

I managed and executed the annotation of construction site images for helmet detection using bounding boxes in LabelImg. The project required effective data preprocessing, annotation for edge cases such as occlusion, and close integration with model tuning for improved performance. I also contributed to creating a structured dataset to boost object detection accuracy for YOLOv8 models. • Processed and annotated 1,500+ images with bounding boxes for object detection. • Optimized annotation methods to address challenges in occluded and complex backgrounds. • Coordinated annotation and model tuning to improve detection metrics. • Ensured labeling consistency and quality through iterative reviews.

2025 - 2025

Large Model Algorithm Intern – Data Annotation & Training

LabelImgImageObject Detection

I performed large-scale image annotation and quality control to support AI large model training, focusing on data accuracy and establishing labeling standards. My responsibilities included the creation and refinement of thousands of labeled samples and the drafting and enforcement of standard annotation guidelines. Regular audits and verification steps ensured the data was both high-quality and suitable for improving AI model performance. • Labeled over 1,000 images for AI model training and validation. • Defined and implemented standardized annotation workflows and guidelines for consistency. • Conducted quality audit cycles for labeled image datasets. • Collaborated with the team to troubleshoot and resolve ambiguous labeling scenarios.

2025 - 2025

Education

Work History