Magellium attends the BiDS'17 (Big Data from Space) conference. This was a great place to share and discuss about deep learning applications for remote sensing.
Software development & system integration 30 % Energy & Transport 10 % Others 30 % Space Consulting & technical support 30 % Defense & Security 20/09/2017
PhD , 1 per BU (EO/GEO/IA) 7 engineers involved Aims Develop Deep Learning in Magellium’s business Back units on key technologies and projects Knowledge Data Data Knowledge Before DL After DL Market Verdict Partial Collapse
(Haïti) Airborne imagery Deep Feed Forward 95% good classifications Internship for Airbus DS – Isolated building detection (Australia) Imagery OneAtlas Deep Convolutional Network 95% good classification
content of vegetated areas Preliminary results 15% more accurate than state-of-the art methods, Sentinel-2 direct application Super-resolution Exploiting time series for resolution improvement Ground occupation (agriculture) Culture type classification Lidar data classification Vegetation monitoring (network operators) Detection and recognition of targets in videos Car industry, robotics, defense