Company description
Established in 2018, AGENIUM Space
(AGS) aims to develop Value-Added-Services for space industry by leveraging edge-AI technologies. The company’s founders bring decades of combined experience in satellite imagery processing and artificial intelligence.
With help of projects accomplished from CNES, ESA and Occitanie support, ESA, Horizon2030, Copernicus Contributing Missions and others, today AGENIUM Space stands proudly offering wide range of products and services for edge-AI adopters in commercial, institutional and military domains.
AGENIUM Space is based in Toulouse (FRANCE) and is part of AGENIUM Group, which has offices in Toulouse, Saint-Germain-en-Laye and Rennes.
Products
Airplane detection – AGS has built a DNN that allows airplane detection in satellite images. It is trained with satellite images where airplanes are aground in airports as well as in flight, observed at various backgrounds like, sea, deserts, islands, snowy mountains and other kinds of complex terrain.
Forest segmentation – AGS’s DNN does forest segmentation — classifying each pixel in satellite image if it is a part of forest or not. This allows easy counting of forested areas, globally.
Destroyed building detection - AGS has created DNN to detect devastated buildings and assess severity of destruction. The algorithm uses a two-step procedure: building recognition and change-detection, with the last part using a historic image of the same area.
Cloud masking - AGS offers two options for cloud applications: cloud and cloud+snow detections (pixelwise segmentations). Thus, output of image processing is a mask specifying category of each pixel. This allows convenient cloud coverage estimation per image and masking the useless parts prior to compression and download.
Ship detection - AGS has developed DNN that can find ships in raw images onboard satellite. This creates technical feasibility for satellite operators to find and monitor anything in waters globally, without a need to retrieve terabytes of useless empty water surface images to ground.