AI Technologies
GeoAI & Spatial Intelligence
Analysing spatial information intelligently and combining it with visual and other data.
Our own tool
GeoAI and Image Annotation with Acotate 2.0 AERO
Our annotation tool for aerial images combines automatic pre-annotation with human correction – the basis for image segmentation that learns.
Starting point
Machine learning in image analysis needs reference data. Creating it by hand is the most labour-intensive part of a GeoAI project.
Approach
- Aerial images are displayed and annotated in polygon format
- Automatic pre-annotation provides the starting point
- A human corrects and approves
- Every correction improves the model for the next pass
What is in place
- Semantic segmentation with a convolutional network of the U-Net architecture
- End-to-end process from data collection through annotation and training to validation
Acotate 2.0 AERO is one building block in an end-to-end GeoAI process: capture requirements, collect and version training data, annotate, train, validate, adapt to the area of use, deploy and improve in operation. We describe the process under Visual and Spatial Data Analysis.
Further topics
AI Technologies
Vision AI
Image-based and video-based AI, grown out of many years of experience in industrial machine vision.
Solutions
Visual and Spatial Data Analysis
Analysing aerial and satellite images with AI, recognising spatial relationships, and turning geodata into concrete insights.
Industries
Geoinformation, Environment and Infrastructure
Analyse aerial and satellite images, link spatial data and build digital representations of infrastructure and surroundings.
Would you like to make AI usable in your company?
Whether a first AI adoption or a complex development task – we discuss the requirements and suitable next steps with you.