We analyse aerial images of agricultural fields captured by drones and label them using semantic segmentation technique.
AI in forests which is keeping an eye on forests and trees making it easier and effective to ensure less to no loss for them. Illegal deforestation or forest fires, all such activities can be detected with AI-enabled systems. Annotating such actions in the images helps them to train the AI model for accurate detection and equip forest management.
AI companies working on improving efficiency of the construction processes from planning to monitoring during actual construction.Enhancing safety of human workers in construction sites using AI is starting to gain prominence among most large construction firms.With our annotation services, you can analyse and label spatial data like satellite images and visual GPS data.
Architects and Civil Engineers are using AI for geospatial machine learning for urban development and management. TagX provides the best quality training data sets to train such AI and ML models that can be used for urban cities or township planning, development and management.
Get annotated satellite images, or Aerial images for drone training, AI camera for traffic monitoring and land area mapping or defining the street routes labeled with precise and accurate image annotation techniques.
With enormous amounts of good quality datasets, AI can predict the occurrence of numerous natural disasters, which can be the difference between life and death for thousands of people.
We analyse pre and post aerial images of disaster-hit locations and label structures like buildings, ports, utility sheds, etc. for enabling smart and effective disaster management projects.
Get training data for you AI
Our experts define strategic business objectives and outcomes of the project
Data is collected using various technologies with inhouse expertise as per requirement
The team is trained & annotations are performed to extract meaningful insights for training AI
The data goes through stringent quality checks and sent for final deployment to meet the threshold accuracy
