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Author (up) Giacomo Magnifico; Beata Megyesi; Mohamed Ali Souibgui; Jialuo Chen; Alicia Fornes
Title Lost in Transcription of Graphic Signs in Ciphers Type Conference Article
Year 2022 Publication International Conference on Historical Cryptology (HistoCrypt 2022) Abbreviated Journal
Volume Issue Pages 153-158
Keywords transcription of ciphers; hand-written text recognition of symbols; graphic signs
Abstract Hand-written Text Recognition techniques with the aim to automatically identify and transcribe hand-written text have been applied to historical sources including ciphers. In this paper, we compare the performance of two machine learning architectures, an unsupervised method based on clustering and a deep learning method with few-shot learning. Both models are tested on seen and unseen data from historical ciphers with different symbol sets consisting of various types of graphic signs. We compare the models and highlight their differences in performance, with their advantages and shortcomings.
Address Amsterdam, Netherlands, June 20-22, 2022
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 HystoCrypt
Notes DAG; 600.121; 600.162; 602.230; 600.140 Approved no
Call Number Admin @ si @ MBS2022 Serial 3731
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