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European Conference on Advances in Databases and Information Systems

ADBIS 2018: New Trends in Databases and Information Systems pp 391–401Cite as

Similarity Queries on Script Image Databases

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 909))

Abstract

For a long time, researchers and archaeologists have studied evolution and similarity among ancient scripts. The vast image libraries which have recently become available allow for data mining to enable the study of evolution of these ancient scripts. In particular, the origin of the Indus Valley script is highly debated and is considered an undeciphered script. In this paper, we use convolutional neural networks to test which alphabets/symbols from various languages may be related to the Indus Valley script. The languages focused on include the Proto-Elamite script and Sumerian.

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Author information

Authors and Affiliations

  1. University of Nebraska-Lincoln, Lincoln, NE, 68588, USA

    Shruti Daggumati

Authors
  1. Shruti Daggumati
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Correspondence to Shruti Daggumati .

Editor information

Editors and Affiliations

  1. Eötvös Loránd University, Budapest, Hungary

    András Benczúr

  2. Abt. Informatik, Universität Kiel, Kiel, Germany

    Bernhard Thalheim

  3. Eötvös Loránd University, Budapest, Hungary

    Tomáš Horváth

  4. Politecnico di Torino, Turin, Italy

    Silvia Chiusano

  5. Polytechnic University of Turin, Turin, Italy

    Tania Cerquitelli

  6. Hungarian Academy of Sciences, Budapest, Hungary

    Csaba Sidló

  7. University of Nebraska–Lincoln, Lincoln, NE, USA

    Peter Z. Revesz

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Daggumati, S. (2018). Similarity Queries on Script Image Databases. In: Benczúr, A., et al. New Trends in Databases and Information Systems. ADBIS 2018. Communications in Computer and Information Science, vol 909. Springer, Cham. https://doi.org/10.1007/978-3-030-00063-9_36

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  • DOI: https://doi.org/10.1007/978-3-030-00063-9_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00062-2

  • Online ISBN: 978-3-030-00063-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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