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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume X-M-1-2023
https://doi.org/10.5194/isprs-annals-X-M-1-2023-207-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-annals-X-M-1-2023-207-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
23 Jun 2023
| 23 Jun 2023
EXPLAINING AI: UNDERSTANDING DEEP LEARNING MODELS FOR HERITAGE POINT CLOUDS
F. Matrone
Department of Environmental, Land and Infrastructure Engineering (DIATI), Politecnico di Torino, 10129, Torino, Italy
A. Felicetti
Department of Information Engineering (DII), Università Politecnica delle Marche, 60131 Ancona, Italy
M. Paolanti
Vision Robotics and Artificial Intelligence Lab (VRAI), Department of Political Sciences, Communication and International Relations, - University of Macerata, 62100 Macerata, Italy
R. Pierdicca
Department of Civil, Building Engineering (DICEA), Università Politecnica delle Marche, 60131 Ancona, Italy
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Short summary
Short summary
For the processing of geomatics data, artificial intelligence (AI) offers overwhelming opportunities. The integration of AI approaches in geomatics has developed into the concept of geospatial artificial intelligence (GeoAI), which is a new paradigm for geographic knowledge discovery and beyond. This contribution outlines AI-based techniques for analysing and interpreting complex geomatics data. How AI approaches have been exploited for the interpretation of geomatic data is explained.
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The International Society for Photogrammetry and Remote Sensing is a non-governmental organization devoted to the development of international cooperation for the advancement of photogrammetry and remote sensing and their applications. The Society operates without any discrimination on grounds of race, religion, nationality, or political philosophy.
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