Lidar Annotation
Training Data provides a full cycle of work on marking lidar clouds to create high-quality training datasets
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It uses a laser beam to measure distances to surrounding objects and create a point cloud representing a 3D map of the scene. Labeling LiDAR point clouds involves identifying and classifying objects using data obtained from the LiDAR sensor.
Lidar (Light Detection and Ranging)
Point Cloud
A point cloud is a set of three-dimensional coordinate points that describe the geometry and location of objects in a scene
3D Object Recognition
Processing of point clouds, three-dimensional models and voxel grids obtained from lidars, stereo cameras or structured light scanners
Terrain modeling
Analysis and processing of data such as altitude maps, laser scans, aerial images to describe the shape and characteristics of the earth's surface and objects
Path Planning and Navigation
Determining the best way to reach the destination, including analysis and consideration of factors: obstacles, road conditions, travel time and user preferences
Change Detection
Detection and classification of changes: deforestation, expansion of buildings, soil erosion, changes in water bodies and other important changes for environmental assessment and management
Virtual Reality and Simulation
Tasks such as gesture recognition, object classification in virtual space, behavioral modeling to develop adaptive responses to user actions
Object Detection
Identification and classification of objects of various types, such as cars, pedestrians, cyclists, buildings, road markings, signs, trees, etc.
Semantic Segmentation
Dividing lidar clouds into small components and determining which classes these components belong to for a deeper understanding of AI systems of the environment
Stages of work
Leave a request on the website for a free consultation with an expert. The account manager will guide you on the services, timelines, and price.
Free pilot:
We will conduct a test pilot project for you and provide a golden set, based on which we will determine the final technical requirements and approve project metrics.

We prepare a contract and all necessary documentation upon the request of your accountants and lawyers.
Workflow customization:
We form a pool of suitable tools and assign an experienced manager who will be in touch with you regarding all project details.
Quality control:
Data uploads for verification are done iteratively, allowing your team to review and approve collected/annotated data.
You pay for the work after receiving the data in agreed quality and quantity.
24 hours
Conducting a pilot 
You pay for the work after you have received the data in the established quality and quantity

Carrying out work on the project
Quality control
from 1 to 5 days
from 1 day to several years
from 1 to 5 days
24 hours
1 to 3 days
Training Data Pro
Expert Team:
Flexible and Scalable Solutions:
Quality Assurance:
Data Security and Confidentiality:
Enhanced Data Accuracy
Consistency in Labels
Reliable Ground Truth
Mitigation of Annotation Biases
Cost and Time Efficiency
GDPR Compliance
Non-disclosure agreement
Data Encryption
Multiple data storage options
Access Controls and Authentication
35 top project managers
100% post payment
$550 minimum check
24/7 availability of customer service
6 years in industry
Variable Workload
Customized Solutions
40+ languages
100+ countries
250k+ assessors
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