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Author Arnau Baro; Jialuo Chen; Alicia Fornes; Beata Megyesi
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 Series Title Abbreviated Series Title
Series Volume Series Issue Edition
Area Expedition Conference (up) DATeCH
Notes DAG; 600.097; 600.140; 600.121 Approved no
Call Number Admin @ si @ BCF2019 Serial 3276
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