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  Deep learning for historical Cadastral maps and satellite imagery analysis: insights from Styria's Franciscean Cadastre

Göderle, W. T., Rampetsreiter, F., Macher, C., Mauthner, K., & Pimas, O. (2024). Deep learning for historical Cadastral maps and satellite imagery analysis: insights from Styria's Franciscean Cadastre. Digital humanities quarterly: DHQ, 18(3): 744.

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Genre: Zeitschriftenartikel

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 Urheber:
Göderle, Wolfgang Thomas1, Autor                 
Rampetsreiter, Fabian, Autor
Macher, Christian, Autor
Mauthner, Katrin, Autor
Pimas, Oliver, Autor
Affiliations:
1Department of Structural Changes of the Technosphere, Max Planck Institute of Geoanthropology, Max Planck Society, ou_3490027              

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 Zusammenfassung: Cadastres from the 19th century are a complex as well as rich source for historians and archaeologists, the study of which presents great challenges. For archaeological and historical remote sensing, we have trained several Deep Learning models, CNNs, and Vision Transformers to extract large-scale data from this knowledge representation. We present the principle results of our work here and demonstrate our browser-based tool that allows researchers and public stakeholders to quickly identify spots that featured buildings in the 19th century Franciscean cadastre. The tool not only supports scholars and fellow researchers in building a better understanding of the settlement history of the region of Styria; it also helps public administration and fellow citizens to swiftly identify areas of heightened sensibility with regard to the cultural heritage of the region.

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Sprache(n): eng - English
 Datum: 2024-082024
 Publikationsstatus: Erschienen
 Seiten: 13
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: State of Research
Objective
Approach
Results
Next Steps
Conclusion
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: URN: http://www.digitalhumanities.org/dhq/vol/18/2/000744/000744.html
Anderer: gea0284
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Titel: Digital humanities quarterly : DHQ
  Andere : DHQ: Digital humanities quarterly
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: Providence, RI : Alliance of Digital Humanities Organizations
Seiten: - Band / Heft: 18 (3) Artikelnummer: 744 Start- / Endseite: - Identifikator: ISSN: 1938-4122
CoNE: https://pure.mpg.de/cone/journals/resource/1938-4122