Artefact-Features Analysis Tool v1.0 (AFAT1)

Link:
Autor/in:
Verlag/Körperschaft:
Universität Hamburg
Erscheinungsjahr:
2022
Medientyp:
Software
Schlagworte:
  • Software Tool
  • Pattern Analysis
  • Statistics
  • Euclidean Distance
Beschreibung:
  • This software tool has been developed by Dr. Hussein Mohammed as a part of sub-project RFA05: Pattern Recognition in 2D Data from Digitised Images and Advanced Aquisition Techniques.

    The main goal of this software tool is to analyse artefact features in order to extract some statistical information such as the mean, standard deviation and outliers. The main tasks achieved by this software tool are:

    • Calculating individual statistics for each entry in the table
    • Calculating general statistics for each table as a whole
    • Calculating distances between different tables

    Acknowledgement:

    The research for this work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy – EXC 2176 ‘Understanding Written Artefacts: Material, Interaction and Transmission in Manuscript Cultures', project no. 390893796. The research was conducted within the scope of the Centre for the Study of Manuscript Cultures (CSMC) at Universität Hamburg.

    The analysis in this application has been developed in close collaboration with Dr. Wiebke Beyer from the CSMC , Hamburg. Furthermore, I would like to thank her for testing the application and validating the results.

  • {"references": ["Mohammed, H., Helman-Wazny, A., Colini, C., Beyer, W., Bosch, S. (2022). Pattern Analysis Software Tools (PAST) for Written Artefacts. In: Uchida, S., Barney, E., Eglin, V. (eds) Document Analysis Systems. DAS 2022. Lecture Notes in Computer Science, vol 13237. Springer, Cham. https://doi.org/10.1007/978-3-031-06555-2_15"]}
Beziehungen:
DOI 10.25592/uhhfdm.9778
Lizenzen:
  • https://creativecommons.org/licenses/by/4.0/legalcode
  • info:eu-repo/semantics/openAccess
Quellsystem:
Forschungsdatenrepositorium der UHH

Interne Metadaten
Quelldatensatz
oai:fdr.uni-hamburg.de:9779