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Silvi Anggraini

Silvi Anggraini

AI Evaluation & Data Annotation Specialist for Vision and LLM Tasks

INDONESIA flag
Wonogiri, Indonesia
$4.00/hrIntermediateAppenClickworkerCVAT

Key Skills

Software

AppenAppen
ClickworkerClickworker
CVATCVAT
iMeritiMerit
MindriftMindrift
OneFormaOneForma
TolokaToloka

Top Subject Matter

No subject matter listed

Top Data Types

AudioAudio
Geospatial Tiled ImageryGeospatial Tiled Imagery
TextText

Top Label Types

Bounding Box
Data Collection
Evaluation Rating
Object Detection
Polyline

Freelancer Overview

I am an AI Training and Data Annotation Specialist with hands-on experience evaluating search engine results, analyzing user intent, assessing prompt quality, and comparing chatbot responses for accuracy, clarity, and relevance. My work requires strict attention to detail, consistency, and the ability to follow complex guidelines—skills that directly support high-quality data labeling for both language and computer vision tasks. In addition to my AI evaluation background, I have practical experience in structured data handling through administrative and audit-related roles, where I performed data entry, document verification, and accuracy checks. This combination of AI evaluation expertise and strong data management skills makes me well-equipped for image, video, and text annotation projects across various domains, including computer vision, self-driving datasets, and LLM refinement.

IntermediateIndonesianJavaneseEnglish

Labeling Experience

OneForma

Computer Vision Image Annotation Project

OneformaImageBounding Box
I worked on an image annotation project focused on sports analytics and athlete performance data. The scope of the project involved labeling sports images by identifying athletes, equipment, field markings, and key action-related elements. Specific tasks included drawing precise bounding boxes and polygons around players, annotating body positions, classifying action types, and tagging relevant contextual details based on detailed annotation guidelines. The project covered several hundred images across multiple sports categories, requiring consistent labeling to support action recognition and computer vision model training. Throughout the project, I adhered to strict quality measures such as accuracy thresholds, consistency checks, cross-review processes, and guideline compliance. My work ensured that every annotation met the required precision level to support high-quality model development in sports analytics and motion understanding.

I worked on an image annotation project focused on sports analytics and athlete performance data. The scope of the project involved labeling sports images by identifying athletes, equipment, field markings, and key action-related elements. Specific tasks included drawing precise bounding boxes and polygons around players, annotating body positions, classifying action types, and tagging relevant contextual details based on detailed annotation guidelines. The project covered several hundred images across multiple sports categories, requiring consistent labeling to support action recognition and computer vision model training. Throughout the project, I adhered to strict quality measures such as accuracy thresholds, consistency checks, cross-review processes, and guideline compliance. My work ensured that every annotation met the required precision level to support high-quality model development in sports analytics and motion understanding.

2024 - 2024

Education

U

Universitas Sebelas Maret

Bachelor of Science, Accounting

Bachelor of Science
2023

Work History

K

KAP Wartono & Rekan

Intern

Surakarta
2022 - 2022
D

Dinas Pendidikan dan Kebudayaan Kabupaten Wonogiri

Practical Trainee

Wonogiri
2019 - 2019