Dane Manuel

Key Skills

Software

Appen

Clickworker

Top Subject Matter

No subject matter listed

Top Data Types

Image

Medical Dicom

Text

Top Task Types

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Classification

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Segmentation

Translation Localization

Freelancer Overview

With over 5 years of freelance experience in data labeling, I have developed a strong expertise in keypoint annotation and image labeling for AI and computer vision projects. I am proficient in using CVAT for annotating human pose, facial keypoints, and object detection, ensuring high accuracy and consistency across thousands of images. My skills extend to Python scripting for preprocessing and automating parts of the labeling process, as well as exporting data in formats like CSV for seamless integration into machine learning pipelines. Notable projects include annotating keypoints for human pose estimation in fitness applications, creating facial landmark datasets for facial recognition, and labeling object keypoints for robotics research. My ability to work independently, adapt to custom annotation schemas, and maintain high-quality control has consistently supported the successful development of AI models in diverse domains, making me a reliable partner for any data labeling or AI training data needs

Labeling Experience

Data annotation

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This project involved annotating a large dataset of images for human pose estimation to support the development of a fitness application. The goal was to create a model that could analyze user posture in real-time and provide corrective feedback for exercises. Using CVAT, I labeled keypoints across human bodies, such as joints, shoulders, and limbs, to identify key poses and movements. The annotated data was exported in CSV format, facilitating easy integration into the model training pipeline. Key Contributions: Keypoint Annotation: Labeled critical body parts (e.g., elbows, knees, wrists) to train an AI system for accurate human pose detection. Data Integrity: Ensured consistency and quality by following strict annotation guidelines and performing regular quality control checks. Tool Utilization: Leveraged CVAT for large-scale annotation tasks and Python for data preprocessing to streamline workflows. Collaboration: Worked closely with developers and AI engineers to ensure the d

This project involved annotating a large dataset of images for human pose estimation to support the development of a fitness application. The goal was to create a model that could analyze user posture in real-time and provide corrective feedback for exercises. Using CVAT, I labeled keypoints across human bodies, such as joints, shoulders, and limbs, to identify key poses and movements. The annotated data was exported in CSV format, facilitating easy integration into the model training pipeline. Key Contributions: Keypoint Annotation: Labeled critical body parts (e.g., elbows, knees, wrists) to train an AI system for accurate human pose detection. Data Integrity: Ensured consistency and quality by following strict annotation guidelines and performing regular quality control checks. Tool Utilization: Leveraged CVAT for large-scale annotation tasks and Python for data preprocessing to streamline workflows. Collaboration: Worked closely with developers and AI engineers to ensure the d

2021 - 2024

Education

Work History