Sanjit Das

Key Skills

Software

CVAT

Top Subject Matter

Vehicle detection for autonomous vehicles

Top Data Types

Image

Video

3D Sensor

Top Task Types

Bounding Box

Classification

Polygon

Segmentation

Freelancer Overview

Data Labeler & Image Annotation Specialist. Core strengths include CVAT. Education includes Higher Secondary Certificate, [mohipal govt collage]. AI-training focus includes data types such as Image and labeling workflows including Bounding Box.

Labeling Experience

Animal Classification Project

CVATImageClassification

Categorized and annotated 200+ wildlife images with bounding boxes and multi-class labels for use in training image classification models. Ensured high accuracy and thorough coverage for diverse animal species during annotation. Contributed to multi-class model development by supplying precisely labeled datasets. • Utilized CVAT for efficient annotation workflow • Labeled a variety of wildlife categories clearly and consistently • Focused on diverse and accurate class assignments • Supported training for multi-class image classification AI models

Categorized and annotated 200+ wildlife images with bounding boxes and multi-class labels for use in training image classification models. Ensured high accuracy and thorough coverage for diverse animal species during annotation. Contributed to multi-class model development by supplying precisely labeled datasets. • Utilized CVAT for efficient annotation workflow • Labeled a variety of wildlife categories clearly and consistently • Focused on diverse and accurate class assignments • Supported training for multi-class image classification AI models

Not specified

Pedestrian Detection Annotation

CVATImageBounding Box

Labeled and annotated 300+ street scene images focusing on pedestrians, cyclists, and traffic signs for AI person detection projects. Applied bounding boxes with a focus on achieving zero missed objects per quality review standards. Strictly adhered to established annotation guidelines ensuring high-quality and consistent results. • Used CVAT for accurate and efficient labeling • Followed detailed annotation guidelines to maximize accuracy • Ensured every image received comprehensive review • Prioritized safety-critical object categories

Labeled and annotated 300+ street scene images focusing on pedestrians, cyclists, and traffic signs for AI person detection projects. Applied bounding boxes with a focus on achieving zero missed objects per quality review standards. Strictly adhered to established annotation guidelines ensuring high-quality and consistent results. • Used CVAT for accurate and efficient labeling • Followed detailed annotation guidelines to maximize accuracy • Ensured every image received comprehensive review • Prioritized safety-critical object categories

Not specified

Vehicle Detection Dataset Image Annotation

CVATImageBounding Box

Annotated over 500 vehicle images with precise bounding boxes for object detection tasks using CVAT. Ensured labeling accuracy exceeded 95% by strictly following annotation guidelines for autonomous vehicle AI training projects. Performed quality checks to validate that each labeled dataset met industry standards for AI reliability. • Applied bounding boxes around cars, trucks, motorcycles, and buses • Maintained high accuracy requirements and minimized errors • Utilized CVAT tool proficiently for all annotation work • Managed high-volume labeling tasks efficiently

Annotated over 500 vehicle images with precise bounding boxes for object detection tasks using CVAT. Ensured labeling accuracy exceeded 95% by strictly following annotation guidelines for autonomous vehicle AI training projects. Performed quality checks to validate that each labeled dataset met industry standards for AI reliability. • Applied bounding boxes around cars, trucks, motorcycles, and buses • Maintained high accuracy requirements and minimized errors • Utilized CVAT tool proficiently for all annotation work • Managed high-volume labeling tasks efficiently

Not specified

Education

Work History