We are excited to share the results of the SpaceNet 9 Challenge! 🛰️ Participants utilized innovative approaches to develop models for optical and SAR satellite image registration. 💡 Details of the top solutions will be shared in an upcoming paper. 🏆 $50,000 in prizes were awarded to the top 5 performing solutions and top academic participants. Congratulations to the winners and thanks to all participants! https://lnkd.in/e-dF7TvH
SpaceNet
Technology, Information and Internet
A partnership initiative dedicated to accelerating open-source applied AI/ML research for geospatial applications.
About us
SpaceNet was founded by IQT Labs’ CosmiQ Works and Maxar (then DigitalGlobe) in August 2016. This informal collaboration aimed to accelerate open-source machine learning capabilities specifically for geospatial use cases, offering a repository of freely available imagery with co-registered map features. Before SpaceNet, computer vision researchers had minimal options to obtain free, precision-labeled and high-resolution satellite imagery. Today, SpaceNet hosts datasets developed by its own team, along with data sets from projects such as IARPA’s Functional Map of the World (fMoW).
- Website
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https://spacenet.ai
External link for SpaceNet
- Industry
- Technology, Information and Internet
- Company size
- 2-10 employees
- Type
- Partnership
- Founded
- 2016
- Specialties
- Remote Sensing, Machine Learning, AI, Artificial Intelligence, Open Source, and Open Data
Employees at SpaceNet
Updates
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Attention Students 🎓: Want to build algorithms for disaster response? Join #SpaceNet9 to align satellite imagery and unlock faster insights. $50K in overall prizes including $2,500 for both the top undergraduate and graduate student participants. Sign up here: https://lnkd.in/eY4cGVs3 https://lnkd.in/dyZAwi48
How do we accelerate disaster response with AI? By solving a critical challenge: aligning different types of satellite imagery. When disasters strike, optical and SAR images offer vital insights—but they don’t naturally align. That slows down damage detection when time matters most. Topcoder is proud to host SpaceNet 9, an impactful challenge now live on our platform, tackling this problem head-on. In partnership with Maxar Technologies, Amazon Web Services (AWS), Umbra, Oak Ridge National Laboratory and IEEE Geoscience and Remote Sensing Society (GRSS) we’re challenging the Topcoder community to develop algorithms that align SAR and optical imagery at the pixel level. - The goal: faster, more accurate disaster analysis - $50,000 in prizes - Deadline: May 26, 2025 Together, we can turn satellite data into life-saving insights. Register here: https://lnkd.in/emQ29ZXF #Topcoder #GeospatialAI #SpaceNet9 #SatelliteImagery
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The SpaceNet 9: Cross-Modal Satellite Imagery Registration challenge is underway! Compete for $50,000 in prizes to develop algorithms that align optical and SAR satellite imagery to help speed up analysis for disaster response. Join today: https://lnkd.in/eY4cGVs3
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