Key Skills

Software

Label Studio

Toloka

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Task Types

Data Collection

Emotion Recognition

Evaluation Rating

Object Detection

Prompt Response Writing SFT

Freelancer Overview

With extensive experience in data labeling and AI training, I specialize in annotating data for computer vision projects, including image and video annotation. I have worked on a variety of projects, training AI systems across industries such as movie creation, mobile apps, and entertainment. My expertise includes the precise labeling of complex datasets, ensuring high-quality inputs for machine learning models. I am skilled in using various annotation tools and techniques, such as object detection, classification, and segmentation. My attention to detail and ability to handle large-scale datasets make me an ideal candidate for any AI training project. Additionally, I am committed to continuous learning and staying updated with the latest advancements in AI technologies to ensure top-tier data quality.

Labeling Experience

Data Labeller

Label StudioVideoSegmentationClassification

In this project, I worked as a data labeler to annotate video datasets for emotion recognition, contributing to the development of a video foundational model. Using Label Studio, I performed precise labeling for various emotional expressions and reactions in video footage. The labeling tasks included segmentation, classification, and emotion recognition, ensuring that the model could accurately understand human emotions based on visual cues. This project involved carefully analyzing video clips and marking specific frames where emotions like happiness, anger, and sadness were expressed, all while adhering to strict quality standards. My work helped in creating a robust AI model that enhances emotional intelligence for various applications, including virtual assistants, customer service bots, and other AI-driven platforms requiring human emotional understanding.

In this project, I worked as a data labeler to annotate video datasets for emotion recognition, contributing to the development of a video foundational model. Using Label Studio, I performed precise labeling for various emotional expressions and reactions in video footage. The labeling tasks included segmentation, classification, and emotion recognition, ensuring that the model could accurately understand human emotions based on visual cues. This project involved carefully analyzing video clips and marking specific frames where emotions like happiness, anger, and sadness were expressed, all while adhering to strict quality standards. My work helped in creating a robust AI model that enhances emotional intelligence for various applications, including virtual assistants, customer service bots, and other AI-driven platforms requiring human emotional understanding.

2023 - 2024

Data Labeller

TolokaImageSegmentationClassification

In this project, I worked as a data labeler for an entertainment app, focusing on image data labeling tasks. Using Toloka, I was responsible for classifying and annotating images based on various attributes, including object detection, emotion recognition, and action recognition. The project required detailed segmentation and classification to help train AI systems in identifying and processing different visual elements within images, such as emotions, actions, and objects. The project involved working with a large dataset, ensuring high-quality and accurate annotations to support the app's image processing and machine learning models. My work contributed to improving the app's ability to analyze user-generated content, enhancing user interaction and overall app experience. The task required precision and a strong understanding of visual context to ensure the AI models performed optimally.

In this project, I worked as a data labeler for an entertainment app, focusing on image data labeling tasks. Using Toloka, I was responsible for classifying and annotating images based on various attributes, including object detection, emotion recognition, and action recognition. The project required detailed segmentation and classification to help train AI systems in identifying and processing different visual elements within images, such as emotions, actions, and objects. The project involved working with a large dataset, ensuring high-quality and accurate annotations to support the app's image processing and machine learning models. My work contributed to improving the app's ability to analyze user-generated content, enhancing user interaction and overall app experience. The task required precision and a strong understanding of visual context to ensure the AI models performed optimally.

2020 - 2023

Education

Work History