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.NET Rocks!

Machine Learning on Geospatial Data with Malte Loller-Anderson & Mathilde Ørstavik

Aug 29, 2024
Malte Loller-Anderson from Norkart specializes in machine learning for geospatial data, while Mathilde Ørstavik focuses on automating the identification of buildings in aerial imagery. They discuss how their models streamline the mapping process by recognizing structures in challenging environments, such as snow and mountainous landscapes. Malte highlights their decision to use in-house nVidia L40 processors instead of cloud solutions, optimizing training times for complex models. Their insights illuminate the future of geospatial technology in urban planning and environmental monitoring.
54:00

Podcast summary created with Snipd AI

Quick takeaways

  • Machine learning plays a critical role in automating the identification of buildings from aerial imagery, significantly improving efficiency and accuracy in mapping.
  • Norkart has opted for in-house training using nVidia L40 processors to ensure ongoing access to powerful resources for complex machine learning models.

Deep dives

Innovations in In-Car Technology

Upgrading in-car technology can significantly enhance the overall driving experience. A recent upgrade by a user included the installation of a new stereo system that features Apple CarPlay and Android Auto, providing seamless connectivity with mobile devices. This new system allows for direct access to navigation apps like Waze, improving route efficiency and providing real-time updates about traffic hazards. In comparison to standard in-car navigation, this system not only offers improved interactive features but also integrates with existing vehicle controls, providing a more connected experience.

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