Viktor Gladkov

Key Skills

Software

CVAT

Label Studio

Roboflow

LabelImg

Top Subject Matter

Computer Vision Practice Projects

Legal Services & Contract Review

Regulatory Compliance & Risk Analysis

Top Data Types

Image

Text

Document

Top Task Types

Bounding Box

Freelancer Overview

I specialize in high-quality image annotation for computer vision and AI/ML projects. I provide precise labeling for object detection, segmentation, and classification tasks to help train accurate machine learning models. Core Skills: Bounding Box Annotation (Object Detection) Polygon & Polyline Annotation Semantic & Instance Segmentation (Masks) Image Classification & Data Labeling Keypoint / Landmark Annotation Annotation Tools: CVAT, Label Studio, Roboflow, LabelImg, MakeSense.ai Output Formats: YOLO / YOLOv8, COCO JSON, Pascal VOC XML, CSV, Segmentation Masks. I deliver accurate, consistent, and scalable annotations tailored to client requirements. Ready to help teams build reliable computer vision models for AI applications such as autonomous driving, security systems, healthcare imaging, and object recognition. - High-quality verified data - Fast and reliable communication

Labeling Experience

Computer Vision Data Annotation (Practice Projects)

CVATImageBounding Box

I annotated computer vision image datasets for object detection and segmentation practice projects. I created accurate bounding boxes and polygon labels following strict dataset guidelines. The goal was to generate high-quality labeled data supporting machine learning model development. • Used CVAT, Label Studio, Roboflow, and LabelImg for annotation processes. • Produced annotations in YOLO and COCO dataset formats. • Ensured consistent labeling accuracy and quality control. • Focused on tasks like object detection, segmentation, and classification.

I annotated computer vision image datasets for object detection and segmentation practice projects. I created accurate bounding boxes and polygon labels following strict dataset guidelines. The goal was to generate high-quality labeled data supporting machine learning model development. • Used CVAT, Label Studio, Roboflow, and LabelImg for annotation processes. • Produced annotations in YOLO and COCO dataset formats. • Ensured consistent labeling accuracy and quality control. • Focused on tasks like object detection, segmentation, and classification.

2024 - Present

Education

Work History