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Seif Waleed

Seif Waleed

Experienced in performing precise data annotation and labeling tasks

Egypt flagcairo, Egypt
$30.00/hrIntermediateOther

Key Skills

Software

Other

Top Subject Matter

Self Driving Car
Autonomous
Agriculture

Top Data Types

3D Sensor
ImageImage
VideoVideo

Top Task Types

Bounding Box
Classification
Land Cover Classification
Polygon
Segmentation

Freelancer Overview

With one year of experience in data labeling and AI training data, you have developed a strong foundation in annotating diverse datasets with precision and accuracy. Your expertise includes working with various data types, such as images, text, and audio, ensuring high-quality annotations that meet project specifications. You have honed your skills in using annotation tools and platforms, which has enabled you to efficiently manage and complete tasks within tight deadlines. What sets you apart is your attention to detail and commitment to maintaining data integrity. You have successfully contributed to projects in industries like healthcare and autonomous vehicles, where your annotations have played a crucial role in training AI models for critical applications. Your ability to adapt to different project requirements and your proactive approach to problem-solving make you a valuable asset in the field of data annotation.

IntermediateArabicEnglish

Labeling Experience

QC Tecnical

OtherImageBounding BoxPolygon
Data Collection: Gather extensive datasets from various sensors, including cameras, LiDAR, radar, and ultrasonic sensors. These datasets should cover diverse driving conditions, scenarios, and edge cases to ensure robustness and adaptability. Data Annotation: Label the collected data to provide context and meaning. This includes: Image Annotation: Using bounding boxes, polygons, and semantic masks to identify and classify objects like vehicles, pedestrians, and traffic signs. LiDAR Annotation: Annotating 3D point cloud data to distinguish objects and their relative distances

Data Collection: Gather extensive datasets from various sensors, including cameras, LiDAR, radar, and ultrasonic sensors. These datasets should cover diverse driving conditions, scenarios, and edge cases to ensure robustness and adaptability. Data Annotation: Label the collected data to provide context and meaning. This includes: Image Annotation: Using bounding boxes, polygons, and semantic masks to identify and classify objects like vehicles, pedestrians, and traffic signs. LiDAR Annotation: Annotating 3D point cloud data to distinguish objects and their relative distances

2023

Education

N

NC Academy

Bachelor's in Busseines, Busseines

Bachelor's in Busseines
2021 - 2024

Work History

M

Micro Engineering

Labeler

CAIRO
2023 - Present
M

Micro Engineering

QC Tecnical

CAIRO
2023 - Present