Inhaltszusammenfassung

This paper addresses the question of to what extent digital methods and specific tools can be supportive for palaeographic studies of hieratic writing. A common task of palaeographic research is to find visually similar signs. An artificial neural network is used for image analysis of the hieratic sign of the bee (Gardiner L2). Its output values are grouped using the dimensionality reduction technique t-SNE. The expected result represents a group of similar hieratic shapes. It is highlighted ...This paper addresses the question of to what extent digital methods and specific tools can be supportive for palaeographic studies of hieratic writing. A common task of palaeographic research is to find visually similar signs. An artificial neural network is used for image analysis of the hieratic sign of the bee (Gardiner L2). Its output values are grouped using the dimensionality reduction technique t-SNE. The expected result represents a group of similar hieratic shapes. It is highlighted how the palaeographic data must be handled, focusing mainly on the compatibility of born digital data and retro-digitized material. For this purpose, a workflow for the treatment of the material is proposed. Digital palaeography is used to determine shape classes for the hieratic sign of the bee. The paper concludes with reflections on methodology and bias in research within the fields both of Egyptology and digital humanities.» weiterlesen» einklappen

Autoren

Klassifikation

DFG Fachgebiet:
Alte Kulturen

DDC Sachgruppe:
Alte Geschichte, Archäologie