QUANTIFYING UNCERTAINTY IN CLASSIFIED POINT CLOUD DATA FOR GEOSPATIAL APPLICATIONS

zu Verbundenen Objekten

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch

Erschienen in
QUANTIFYING UNCERTAINTY IN CLASSIFIED POINT CLOUD DATA FOR GEOSPATIAL APPLICATIONS ; volume:XLIV-M-2-2020 ; year:2020 ; pages:87-93
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLIV-M-2-2020 (2020), 87-93

Urheber
Sen, S.
Turel, N.

DOI
10.5194/isprs-archives-XLIV-M-2-2020-87-2020
URN
urn:nbn:de:101:1-2020111904185655799147
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
15.08.2025, 07:22 MESZ

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Beteiligte

  • Sen, S.
  • Turel, N.

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