analysis at scale
Training computer vision
algorithms based on virtual synthetic data.
Space is booming.
The amount of new earth-observing satellite constellations keeps on expanding, thus, data from orbit becomes much more available and of better resolutions and revisit rates.
While data availability dramatically expands, scalable image analysis capabilities are becoming vital in order to fully utilize it.
Traditional ‘brute-force’ machine learning methods just don’t do the trick.
Image analysis algorithms generation requires huge amounts of data, which besides being very expensive, takes a lot of time and effort to collect and prepare.
This is not scalable.
Train your machine learning algorithms with realistic, fully annotated virtual synthetic datasets, with a broad range of variations, optimized for training computer vision algorithms.
Use off-the-shelf or easily generate customized image analysis algorithms,
ready to deploy on cloud or on-prem.
Create sophisticated, end to end, applications to monitor, detect and analyze changes, trends, and anomalies.
Save up to 80% of related
cost and effort
Reduce valuable time
from a need to analysis
Easily expand your capabilities to new
areas, new sensors, and objectives