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GeoAI as collaborative effort: interview with Devis Tuia
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0001-5629-0981
Department of Human Geography and Spatial Planning, University Utrecht, Princetonlaan 8a, Utrecht, Netherlands.
Environmental Computational Science and Earth Observation laboratory, Ecole Polytechnique Fédérale de Lausanne, EPFL Valais Wallis, Rue de l’Industrie 17, Case postale 440, Sion, Switzerland.
2023 (English)In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 37, p. 99-105Article in journal, Editorial material (Refereed) Published
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Springer Science+Business Media B.V., 2023. Vol. 37, p. 99-105
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Computer Sciences
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URN: urn:nbn:se:umu:diva-204394DOI: 10.1007/s13218-022-00791-5ISI: 000920535100002Scopus ID: 2-s2.0-85146535351OAI: oai:DiVA.org:umu-204394DiVA, id: diva2:1733782
Available from: 2023-02-03 Created: 2023-02-03 Last updated: 2023-07-13Bibliographically approved

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Richter, Kai-Florian

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