Artwork

Contenuto fornito da Carl Franklin and Richard Campbell, Carl Franklin, and Richard Campbell. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Carl Franklin and Richard Campbell, Carl Franklin, and Richard Campbell o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
Player FM - App Podcast
Vai offline con l'app Player FM !

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

54:00
 
Condividi
 

Manage episode 436743450 series 134848
Contenuto fornito da Carl Franklin and Richard Campbell, Carl Franklin, and Richard Campbell. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Carl Franklin and Richard Campbell, Carl Franklin, and Richard Campbell o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
What can machine learning do for geospatial data? Carl and Richard talk to Malte Loller-Anderson and Mathilde Ørstavik about their work at Norkart, using aerial imagery to build detailed maps around Norway. Mathilde dives into the critical role of machine learning - identifying buildings in images. Usually done by hand with each new image, Norkart has a machine learning model that automates the process trained on previous vector maps of buildings. But there are many things that look like buildings in Norway, including patches of snow, mountains, and even shapes under water. Malte also discusses how Norkart has decided to train in-house with nVidia L40 processors rather than in the cloud - the hardware is used 24 hours a day since some models can take weeks to train! There are many interesting ideas about geospatial data and machine learning from people who have been doing it for years.
  continue reading

556 episodi

Artwork
iconCondividi
 
Manage episode 436743450 series 134848
Contenuto fornito da Carl Franklin and Richard Campbell, Carl Franklin, and Richard Campbell. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Carl Franklin and Richard Campbell, Carl Franklin, and Richard Campbell o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
What can machine learning do for geospatial data? Carl and Richard talk to Malte Loller-Anderson and Mathilde Ørstavik about their work at Norkart, using aerial imagery to build detailed maps around Norway. Mathilde dives into the critical role of machine learning - identifying buildings in images. Usually done by hand with each new image, Norkart has a machine learning model that automates the process trained on previous vector maps of buildings. But there are many things that look like buildings in Norway, including patches of snow, mountains, and even shapes under water. Malte also discusses how Norkart has decided to train in-house with nVidia L40 processors rather than in the cloud - the hardware is used 24 hours a day since some models can take weeks to train! There are many interesting ideas about geospatial data and machine learning from people who have been doing it for years.
  continue reading

556 episodi

Wszystkie odcinki

×
 
Loading …

Benvenuto su Player FM!

Player FM ricerca sul web podcast di alta qualità che tu possa goderti adesso. È la migliore app di podcast e funziona su Android, iPhone e web. Registrati per sincronizzare le iscrizioni su tutti i tuoi dispositivi.

 

Guida rapida