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Author Arnau Baro; Jialuo Chen; Alicia Fornes; Beata Megyesi edit   pdf
doi  openurl
  Title Towards a generic unsupervised method for transcription of encoded manuscripts Type Conference Article
  Year 2019 Publication 3rd International Conference on Digital Access to Textual Cultural Heritage Abbreviated Journal  
  Volume Issue Pages 73-78  
  Keywords A. Baró, J. Chen, A. Fornés, B. Megyesi.  
  Abstract Historical ciphers, a special type of manuscripts, contain encrypted information, important for the interpretation of our history. The first step towards decipherment is to transcribe the images, either manually or by automatic image processing techniques. Despite the improvements in handwritten text recognition (HTR) thanks to deep learning methodologies, the need of labelled data to train is an important limitation. Given that ciphers often use symbol sets across various alphabets and unique symbols without any transcription scheme available, these supervised HTR techniques are not suitable to transcribe ciphers. In this paper we propose an un-supervised method for transcribing encrypted manuscripts based on clustering and label propagation, which has been successfully applied to community detection in networks. We analyze the performance on ciphers with various symbol sets, and discuss the advantages and drawbacks compared to supervised HTR methods.  
  Address Brussels; May 2019  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor (up) Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference DATeCH  
  Notes DAG; 600.097; 600.140; 600.121 Approved no  
  Call Number Admin @ si @ BCF2019 Serial 3276  
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