![]() On today’s pod, CosmiQ’s Ryan Lewis and Dr. However, the SpaceNet 5 challenge made significant progress in this field with top participants being able to extract both road networks and speed/travel time estimates for each roadway. Īp#25 Evaluating SpaceNet 5 Challenge Results: Road Network Detection & Optimized Routingĭespite its application to myriad humanitarian and civil use cases, automated road network extraction from overhead satellite imagery remains quite challenging. SpaceNet is made possible by co-founder and managing partner, CosmiQ Works co-founder and co-chair, Maxar Technologies and all the other Partners: Amazon Web Services (AWS), Capella Space, Topcoder, IEEE Geoscience and Remote Sensing (GRSS), the National Geospatial-Intelligence Agency, and Planet. Hear about the challenge’s winning artificial intelligence models and the tradeoff between inference speed and model performance. In this episode, CosmiQ’s Ryan Lewis, Jake Shermeyer, and Daniel Hogan discuss the SpaceNet 6 Challenge where participants were asked to automatically extract building footprints with computer vision and AI algorithms using a combination of synthetic aperture radar (SAR) and electro-optical imagery. SpaceNet is a non-profit dedicated to accelerating open source, applied research in geospatial machine learning. J#26 SpaceNet 6 Challenge Results: Multi-Sensor All-Weather Mapping SpaceNet is a nonprofit made possible by co-founder and managing partner, CosmiQ Works co-founder and co-chair, Maxar Technologies and all the other Partners: Amazon Web Services (AWS), Capella Space, Topcoder, IEEE Geoscience and Remote Sensing (GRSS), the National Geospatial-Intelligence Agency, and Planet. Finally, the group discusses CosmiQ’s new addition to the Solaris python package: a multi-modal pre-processing library and a new API called ‘PipeSegment’ for seamlessly stringing together different operations. ![]() ![]() Additionally, the podcast also explores the value of frequent SAR revisits that can be beneficial for foundational mapping applications. Learn more about data fusion and deep learning approaches that work to blend synthetic aperture radar (SAR) and optical imagery. Aug#27 SpaceNet 6: The Multi-Modal Extravaganza Family HourĬosmiQ’s Jake Shermeyer and Daniel Hogan are joined by Capella Space’s Jason Brown and IEEE Geoscience and Remote Sensing’s (GRSS) Ronny Hänsch to once again discuss the SpaceNet 6 Dataset and post-challenge experiments. ![]()
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