Manuela Castañeda

Key Skills

Software

CVAT

Labelbox

Label Studio

SuperAnnotate

V7 Labs

Top Subject Matter

Satellite Image Classification

LLM evaluation in Spanish

Image Classification

Top Data Types

Computer Code Programming

Image

Video

Top Task Types

Bounding Box

Classification

Emotion Recognition

Object Detection

Tracking

Freelancer Overview

I am an AI and Computer Vision specialist with hands-on experience in data labeling for machine learning projects. My background includes annotating large-scale datasets for various applications, ranging from image analysis to training deep learning models. I have worked on multiple projects that involve data preparation, model evaluation, and quality control, ensuring high-precision annotations to improve model performance. My expertise spans across different types of data, including images and videos, with a focus on delivering accurate and scalable solutions for AI training.

Labeling Experience

Hidden Object Recognition

V7 LabsImageBounding Box

This project focused on developing AI systems capable of recognizing obscured or partially visible objects in complex environments, such as in security footage or challenging real-world scenarios. My work involved labeling objects that were partially hidden or camouflaged within the scene, requiring meticulous attention to detail. I applied advanced object tracking and segmentation techniques to ensure consistent and accurate labeling, allowing the AI to improve its ability to recognize hidden objects with greater accuracy.

This project focused on developing AI systems capable of recognizing obscured or partially visible objects in complex environments, such as in security footage or challenging real-world scenarios. My work involved labeling objects that were partially hidden or camouflaged within the scene, requiring meticulous attention to detail. I applied advanced object tracking and segmentation techniques to ensure consistent and accurate labeling, allowing the AI to improve its ability to recognize hidden objects with greater accuracy.

2024 - 2024

Forgery Detection

LabelboxVideoClassification

In this multimedia forgery detection project, I contributed to the labeling of tampered images and videos to train AI models that detect manipulations, such as deepfakes or image alterations. The task involved identifying subtle inconsistencies in lighting, shadows, textures, and other visual clues that indicated potential forgery. By providing high-quality annotations, I helped improve the model’s accuracy in detecting even the smallest signs of media manipulation.

In this multimedia forgery detection project, I contributed to the labeling of tampered images and videos to train AI models that detect manipulations, such as deepfakes or image alterations. The task involved identifying subtle inconsistencies in lighting, shadows, textures, and other visual clues that indicated potential forgery. By providing high-quality annotations, I helped improve the model’s accuracy in detecting even the smallest signs of media manipulation.

2024 - 2024

Hyperspectral Imaging

SuperannotateImageFine Tuning

Worked with hyperspectral image datasets, primarily focusing on enhancing data quality for remote sensing and biomedical applications. The project involved labeling distinct spectral signatures across various materials or tissues, allowing machine learning models to identify subtle differences that would be invisible in standard imaging. My role was to apply precise segmentation techniques, ensuring that each pixel in the dataset was accurately labeled to improve the classification and analysis of hyperspectral data.

Worked with hyperspectral image datasets, primarily focusing on enhancing data quality for remote sensing and biomedical applications. The project involved labeling distinct spectral signatures across various materials or tissues, allowing machine learning models to identify subtle differences that would be invisible in standard imaging. My role was to apply precise segmentation techniques, ensuring that each pixel in the dataset was accurately labeled to improve the classification and analysis of hyperspectral data.

2024 - 2024

Biomedical Imaging

SuperannotateImageSegmentation

This project involved labeling and segmenting medical imaging data such as MRI, CT scans, and histopathological images. The goal was to assist in the development of AI models that could support medical diagnostics by identifying regions of interest, such as tumors or other anomalies, with high accuracy. I used advanced annotation tools to ensure precise labeling of both normal and pathological areas, helping the AI models to distinguish between healthy and abnormal tissues effectively.

This project involved labeling and segmenting medical imaging data such as MRI, CT scans, and histopathological images. The goal was to assist in the development of AI models that could support medical diagnostics by identifying regions of interest, such as tumors or other anomalies, with high accuracy. I used advanced annotation tools to ensure precise labeling of both normal and pathological areas, helping the AI models to distinguish between healthy and abnormal tissues effectively.

2023 - 2023

Education

Work History