Resolution varies wildly
A class visible at 5cm may be invisible at 50cm.
Satellite, aerial and UAV imagery
Land use, asset inspection and change detection at survey-grade consistency, across resolutions and seasons.
Aerial datasets are usually built from captures taken months apart, at different altitudes, in different light. The hard part is not labelling one image well — it is labelling the tenth pass the same way as the first, so change detection measures change rather than measuring the labeller.
A class visible at 5cm may be invisible at 50cm.
The same field looks like a different class in a different month.
A single frame can hold thousands of instances.
Labels that drift from their coordinates are worse than no labels.
Semantic segmentation across agricultural, urban and natural cover.
Extraction and change detection for planning and cadastre.
Powerline, pipeline and rail asset condition from UAV capture.
Encroachment detection along corridors.
Rapid damage classification after an event.
Panel detection and roof-suitability annotation.
Tell us what you are building and we will come back with a plan, a sample and a price.