![]() Until now, high-resolution satellite imagery has not been readily accessible for data scientists and developers to build meaningful computer vision algorithms. The industry is coming together to power smarter algorithms so we can see and learn things from imagery about our planet that we simply cannot know today through manual techniques.” “SpaceNet is key to unlocking a huge explosion of new AI-driven applications that ultimately will help us better respond to natural disasters, counter global security threats, improve population health outcomes, and much more. While commercial constellations are poised to collect imagery at global scale, we must advance our ability to analyze data to realize its full potential,” said Tony Frazier, Senior Vice President at DigitalGlobe. SpaceNet aims to facilitate similar advances in automating the detection and extraction of features in satellite imagery, fueled by the massive amount of information about our changing planet that DigitalGlobe collects every day, and that of emerging commercial satellite imagery providers.Įach minute something is happening in the world. Most of this innovation has occurred through research enabled by ImageNet, a database of 14 million photographs labeled in over 20,000 categories. GPU-accelerated deep learning has led to huge breakthroughs in the field of computer vision. SpaceNet is a collaboration between DigitalGlobe, CosmiQ Works, and NVIDIA, and the imagery is now freely available as a public data set on Amazon Web Services, Inc. ![]() ![]() (NYSE: DGI), a leader in earth imagery and information about our changing planet, announced the launch of SpaceNet, an online repository of satellite imagery and labeled training data that will advance the development of machine learning and deep learning algorithms that leverage remote sensing data. ![]()
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