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The missing piece to faster, cheaper and more accurate 3D mapping

A research team from the Geneva School of Economics and Management (GSEM) and the EPF Lausanne have combined artificial intelligence with a new algorithm to create a method that considerably reduces the time and resources needed to accurately scan complex landscapes and potentially holds the key to automated drone mapping. The new method was developed by Davide A. Cucci (GSEM Senior Research Associate), Aurélien Brun, and Jan Skaloud and is detailed in the article, Lidar point–to–point correspondences for rigorous registration of kinematic scanning in dynamic networks, published in the ISPRS Journal of Photogrammetry and Remote Sensing.

> For more information on this research, please consult the web page published by the GSEM: https://www.unige.ch/gsem/en/about/news-events/news/2022/3d-mapping/

ENGLISH
> To read the University of Geneva release, please click on the link
> To read the EPFL article, please click on the link
> To read the Mirage News article, please click on the link
> To read the AZoOptics article, please click on the link
> To read the Eurasia Review article, please click on the link

FRENCH
> To read the communiqué de l’UNIGE, please click on the link
> To read the EPFL article, please click on the link

May 20, 2022
  2022
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