{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T21:42:26Z","timestamp":1778103746023,"version":"3.51.4"},"reference-count":44,"publisher":"Walter de Gruyter GmbH","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,2,26]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p xml:lang=\"en\">The classification of cuneiform signs according to stylistic criteria is a difficult task, which often leaves experts in the field disagree. This study introduces a new publicly available dataset of cuneiform signs classified according to style and Convolutional Neural Network (CNN) approaches to differentiate between cuneiform signs of the two main styles of the first millennium <jats:sc>bce<\/jats:sc>, Neo-Assyrian and Neo-Babylonian. The CNN model reaches an accuracy of 83\u202f% in style classification. This tool has potential implications for the recognition of individual scribes and the dating of undated cuneiform tablets.<\/jats:p>","DOI":"10.1515\/itit-2023-0114","type":"journal-article","created":{"date-parts":[[2024,4,5]],"date-time":"2024-04-05T20:21:02Z","timestamp":1712348462000},"page":"15-27","source":"Crossref","is-referenced-by-count":4,"title":["Stylistic classification of cuneiform signs using convolutional neural networks"],"prefix":"10.1515","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-4478-8376","authenticated-orcid":false,"given":"Vasiliy","family":"Yugay","sequence":"first","affiliation":[{"name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen , Geschwister-Scholl-Platz 1, 80539 Munich , Germany"}]},{"given":"Kartik","family":"Paliwal","sequence":"additional","affiliation":[{"name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen , Geschwister-Scholl-Platz 1, 80539 Munich , Germany"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5715-9979","authenticated-orcid":false,"given":"Yunus","family":"Cobanoglu","sequence":"additional","affiliation":[{"name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen , Geschwister-Scholl-Platz 1, 80539 Munich , Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9107-6574","authenticated-orcid":false,"given":"Luis","family":"S\u00e1enz","sequence":"additional","affiliation":[{"name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen , Geschwister-Scholl-Platz 1, 80539 Munich , Germany"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-1295-4751","authenticated-orcid":false,"given":"Ekaterine","family":"Gogokhia","sequence":"additional","affiliation":[{"name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen , Geschwister-Scholl-Platz 1, 80539 Munich , Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8359-382X","authenticated-orcid":false,"given":"Shai","family":"Gordin","sequence":"additional","affiliation":[{"name":"Ariel University , Kiryat Ha\u2019Mada 3, 40700 Ariel , Israel"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0093-528X","authenticated-orcid":false,"given":"Enrique","family":"Jim\u00e9nez","sequence":"additional","affiliation":[{"name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen , Geschwister-Scholl-Platz 1, 80539 Munich , Germany"}]}],"member":"374","published-online":{"date-parts":[[2024,4,8]]},"reference":[{"key":"2024110207213605445_j_itit-2023-0114_ref_001","unstructured":"M. P. Streck, \u201cGro\u00dfes Fach Altorientalistik: der Umfang des keilschriftlichen Textkorpus,\u201d Mitt. dtsch. Orient-Ges., vol. 142, pp. 35\u201358, 2010."},{"key":"2024110207213605445_j_itit-2023-0114_ref_002","doi-asserted-by":"crossref","unstructured":"M. J. Geller, \u201cReview of Sachs and Hunger, Astronomical diaries 3,\u201d Bull. Sch. Orient. Afr. Stud., vol. 66, pp. 67\u201371, 2003. https:\/\/doi.org\/10.1017\/S0041977X03220061.","DOI":"10.1017\/S0041977X03220061"},{"key":"2024110207213605445_j_itit-2023-0114_ref_003","unstructured":"W. G. Lambert and A. R. Millard, Atra-hasis. The Babylonian Story of the Flood, Oxford, Clarendon Press, 1969."},{"key":"2024110207213605445_j_itit-2023-0114_ref_004","unstructured":"J. J. A. van Dijk, Literarische Texte aus Babylon, Berlin, Akademie-Verlag, 1987."},{"key":"2024110207213605445_j_itit-2023-0114_ref_005","unstructured":"I. M\u00e1rquez Rowe, \u201cTwo Middle Babylonian Atra-hasis tablets from Babylon,\u201d Aula Orientalis, vol. 34, pp. 57\u201370, 2016."},{"key":"2024110207213605445_j_itit-2023-0114_ref_006","unstructured":"J. Peterson, Sumerian Literary Fragments in the University Museum, Philadelphia, Biblioteca del Pr\u00f3ximo Oriente Antiguo, Madrid, Consejo Superior de Investigaciones Cient\u00edficas, 2011."},{"key":"2024110207213605445_j_itit-2023-0114_ref_007","unstructured":"M. Jursa, \u201cLate Babylonian epigraphy: a case study,\u201d in Current Research in Cuneiform Palaeography. Proceedings of the Workshop Organised at the 60th Rencontre Assyriologique Internationale, Warsaw 2014, E. Devecchi, G. G. W. M\u00fcller, and J. Myn\u00e1\u0159ov\u00e1, Eds., Gladbeck, PeWe, 2015, pp. 187\u2013198."},{"key":"2024110207213605445_j_itit-2023-0114_ref_008","doi-asserted-by":"crossref","unstructured":"E. Jim\u00e9nez, Middle and Neo-Babylonian Literary Texts in the Frau Professor Hilprecht Collection, Jena, Wiesbaden, Harrassowitz, 2022. Available at: https:\/\/www.doi.org\/10.13173\/9783447118811.","DOI":"10.13173\/9783447118811"},{"key":"2024110207213605445_j_itit-2023-0114_ref_009","unstructured":"J. C. Fincke, \u201cThe Babylonian texts of Nineveh,\u201d Arch. Orientforsch., vol. 50, pp. 111\u2013149, 2003\u20132004. Available at: https:\/\/www.jstor.org\/stable\/41668620."},{"key":"2024110207213605445_j_itit-2023-0114_ref_010","unstructured":"A. Sahala, \u201cContributions to computational Assyriology,\u201d PhD thesis, 2021. http:\/\/hdl.handle.net\/10138\/332924."},{"key":"2024110207213605445_j_itit-2023-0114_ref_011","doi-asserted-by":"crossref","unstructured":"T. Dencker, P. Klinkisch, S. M. Maul, and B. Ommer, \u201cDeep learning of cuneiform sign\u202fdetection with weak supervision using transliteration alignment,\u201d PLoS One, vol. 15, no. 12, 2020, Art. no. e0243039. https:\/\/doi.org\/10.1371\/journal.pone.0243039.","DOI":"10.1371\/journal.pone.0243039"},{"key":"2024110207213605445_j_itit-2023-0114_ref_012","doi-asserted-by":"crossref","unstructured":"E. Rusakov, et al.., \u201cEmbedded attributes for cuneiform sign\u202fspotting,\u201d in Document Analysis and Recognition \u2013 ICDAR 2021, J. Llad\u00f3s, D. Lopresti, and S. Uchida, Eds., Cham, Springer International Publishing, 2021, pp. 291\u2013305.","DOI":"10.1007\/978-3-030-86331-9_19"},{"key":"2024110207213605445_j_itit-2023-0114_ref_013","unstructured":"E. C. Williams, et al.., \u201cDeepScribe: localization and classification of elamite cuneiform signs via deep learning,\u201d arXiv preprint arXiv:2306.01268, 2023. https:\/\/doi.org\/10.48550\/arXiv.2306.01268."},{"key":"2024110207213605445_j_itit-2023-0114_ref_045","doi-asserted-by":"crossref","unstructured":"Y. Cobanoglu, L. S\u00e1enz, I. Khait, and E. Jim\u00e9nez, \u201cSign detection for cuneiform tablets,\u201d Inf.\u00a0 Technol., vol. 66, no. 1, pp. 25\u201335, 2024.","DOI":"10.1515\/itit-2024-0028"},{"key":"2024110207213605445_j_itit-2023-0114_ref_015","doi-asserted-by":"crossref","unstructured":"Y. Liu, C. Si, K. Jin, T. Shen, and M. Hu, \u201cFCENet: an instance segmentation model for extracting figures and captions from material documents,\u201d IEEE Access, vol. 9, pp. 551\u2013564, 2021. https:\/\/doi.org\/10.1109\/ACCESS.2020.3046496.","DOI":"10.1109\/ACCESS.2020.3046496"},{"key":"2024110207213605445_j_itit-2023-0114_ref_016","unstructured":"M. Tan and Q. V. Le, \u201cEfficientNet: rethinking model scaling for convolutional neural networks,\u201d in Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA, Proceedings of Machine Learning Research, vol. 97, C. Kamalika, and S. Ruslan, 2019, pp. 6105\u20136114. Available at: http:\/\/proceedings.mlr.press\/v97\/tan19a.html."},{"key":"2024110207213605445_j_itit-2023-0114_ref_017","doi-asserted-by":"crossref","unstructured":"A. Hamplov\u00e1, D. Franc, P. Pavl\u00ed\u010dek, A. Romach, and Sh. Gordin, \u201cCuneiform reading using computer vision algorithms,\u201d in Proceedings of the 2022 5th International Conference on Signal Processing and Machine Learning. SPML \u201922, Dalian, China, Association for Computing Machinery, 2022, pp. 242\u2013245.","DOI":"10.1145\/3556384.3556421"},{"key":"2024110207213605445_j_itit-2023-0114_ref_018","doi-asserted-by":"crossref","unstructured":"M. Mahmood, F. M. Jasem, A. A. Mukhlif, and B. Al-Khateeb, \u201cClassifying cuneiform symbols using machine learning algorithms with unigram features on a balanced dataset,\u201d J. Intell. Syst., vol. 32, no. 1, p. 20230087, 2023. https:\/\/doi.org\/10.1515\/jisys-2023-0087.","DOI":"10.1515\/jisys-2023-0087"},{"key":"2024110207213605445_j_itit-2023-0114_ref_019","unstructured":"M. Zampieri, et al.., \u201cA report on the third Vardial evaluation campaign,\u201d in Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects, M. Zampieri, et al.., Eds., Ann Arbor, Michigan, Association for Computational Linguistics, 2019, pp. 1\u201316. Available at: https:\/\/aclanthology.org\/W19-1401."},{"key":"2024110207213605445_j_itit-2023-0114_ref_020","unstructured":"B. Stewart, et al.., \u201cThe DigiPal project for European scripts and decorations,\u201d Essays Stud., vol. 68, pp. 25\u201359, 2015."},{"key":"2024110207213605445_j_itit-2023-0114_ref_021","unstructured":"P. Anthony Stokes, \u201cOn digital and computational humanities for manuscript studies: where have we been, where are we going?,\u201d Manuscr. Cultures, vol. 15, pp. 37\u201346, 2020."},{"key":"2024110207213605445_j_itit-2023-0114_ref_022","doi-asserted-by":"crossref","unstructured":"S. M. Griffin, \u201cEpigraphy and paleography: bringing records from the distant past to the present,\u201d Int. J. Digit. Libr., vol. 24, no. 2, pp. 77\u201385, 2023. https:\/\/doi.org\/10.1007\/s00799-023-00371-4.","DOI":"10.1007\/s00799-023-00371-4"},{"key":"2024110207213605445_j_itit-2023-0114_ref_023","doi-asserted-by":"crossref","unstructured":"M. Kestemont, C. Vincent, and D. Stutzmann, \u201cArtificial paleography: computational approaches to identifying script types in medieval manuscripts,\u201d Speculum, vol. 92.S1, pp. S86\u2013S109, 2017.","DOI":"10.1086\/694112"},{"key":"2024110207213605445_j_itit-2023-0114_ref_046","doi-asserted-by":"crossref","unstructured":"K. Adam, A. Baig, S. Al-Maadeed, A. Bouridane, and Sh. El-Menshawy, \u201cKERTAS: dataset for automatic dating of ancient Arabic manuscripts,\u201d Int. J. Doc. Anal. Recognit., vol. 21, pp. 283\u2013290, 2018. https:\/\/doi.org\/10.1007\/s10032-018-0312-3.","DOI":"10.1007\/s10032-018-0312-3"},{"key":"2024110207213605445_j_itit-2023-0114_ref_025","doi-asserted-by":"crossref","unstructured":"M. Popovi\u0107, M. A. Dhali, and L. Schomaker, \u201cArtificial intelligence based writer identification generates new evidence for the unknown scribes of the Dead Sea Scrolls exemplified by the Great Isaiah Scroll (1QISAA) (1QIsaa),\u201d PloS One, vol. 16, no. 4, 2021, Art. no. e0249769. https:\/\/doi.org\/10.1371\/journal.pone.0249769.","DOI":"10.1371\/journal.pone.0249769"},{"key":"2024110207213605445_j_itit-2023-0114_ref_026","doi-asserted-by":"crossref","unstructured":"J. Pavlopoulos, M. Konstantinidou, I. Marthot-Santaniello, H. Essler, and A. Paparigopoulou, \u201cDating Greek Papyri with text regression,\u201d in Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Association for Computational Linguistics, 2023, pp. 10001\u201310013. Available at: https:\/\/doi.org\/10.18653\/v1\/2023.acl-long.556.","DOI":"10.18653\/v1\/2023.acl-long.556"},{"key":"2024110207213605445_j_itit-2023-0114_ref_027","doi-asserted-by":"crossref","unstructured":"Y. Li, D. Genzel, Y. Fujii, and A. C. Popat., \u201cPublication date estimation for printed historical documents using convolutional neural networks,\u201d in Proceedings of the 3rd International Workshop on Historical Document Imaging and Processing. HIP \u201915, New York, NY, USA, Association for Computing Machinery, 2015, pp. 99\u2013106. Available at: https:\/\/doi.org\/10.1145\/2809544.2809550.","DOI":"10.1145\/2809544.2809550"},{"key":"2024110207213605445_j_itit-2023-0114_ref_028","doi-asserted-by":"crossref","unstructured":"F. Wahlberg, T. Wilkinson, and A. Brun, \u201cHistorical manuscript production date estimation using deep convolutional neural networks,\u201d in 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR), IEEE, 2016, pp. 205\u2013210. Available at: https:\/\/doi.org\/10.1109\/ICFHR.2016.0048.","DOI":"10.1109\/ICFHR.2016.0048"},{"key":"2024110207213605445_j_itit-2023-0114_ref_029","unstructured":"S. Boldsen and F. Wahlberg, \u201cSurvey and reproduction of computational approaches to dating of historical texts,\u201d in Nordic Conference on Computational Linguistics (NoDaLiDa), Sweden, Link\u00f6ping University Electronic Press, 2021, pp. 145\u2013156. Available at: https:\/\/aclanthology.org\/2021.nodalida-main.15."},{"key":"2024110207213605445_j_itit-2023-0114_ref_030","doi-asserted-by":"crossref","unstructured":"I. Rastas, et al.., \u201cExplainable publication year prediction of eighteenth century texts with the BERT model,\u201d in Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change, Dublin, Ireland, Association for Computational Linguistics, 2022, pp. 68\u201377. Available at: https:\/\/doi.org\/10.18653\/v1\/2022.lchange-1.7.","DOI":"10.18653\/v1\/2022.lchange-1.7"},{"key":"2024110207213605445_j_itit-2023-0114_ref_031","doi-asserted-by":"crossref","unstructured":"M. A. Dhali, C. N. Jansen, J. W. de Wit, and L. Schomaker, \u201cFeature-extraction methods for historical manuscript dating based on writing style development,\u201d Pattern Recognit. Lett., vol. 131, pp. 413\u2013420, 2020. https:\/\/doi.org\/10.1016\/j.patrec.2020.01.027.","DOI":"10.1016\/j.patrec.2020.01.027"},{"key":"2024110207213605445_j_itit-2023-0114_ref_032","doi-asserted-by":"crossref","unstructured":"P. F. Jacobs, et al.., \u201cActive learning for reducing labeling effort in text classification tasks,\u201d in Benelux Conference on Artificial Intelligence, Springer, 2021, pp. 3\u201329.","DOI":"10.1007\/978-3-030-93842-0_1"},{"key":"2024110207213605445_j_itit-2023-0114_ref_033","doi-asserted-by":"crossref","unstructured":"L. Lastilla, S. Ammirati, D. Firmani, N. Komodakis, P. Merialdo, and S. Scardapane, \u201cSelf-supervised learning for medieval handwriting identification: a case study from the vatican apostolic library information processing & management,\u201d Inf. Process. Manage., vol. 59, no. 3, p. 102875, 2022. https:\/\/doi.org\/10.1016\/j.ipm.2022.102875.","DOI":"10.1016\/j.ipm.2022.102875"},{"key":"2024110207213605445_j_itit-2023-0114_ref_034","unstructured":"S. H\u00fcgel, \u201cCuneiform Digital Palaeography Project (CDPP) v0.2,\u201d 2014, Version v0.2, https:\/\/doi.org\/10.5281\/zenodo.11647."},{"key":"2024110207213605445_j_itit-2023-0114_ref_035","unstructured":"T. Arvanitis, et al.., \u201cThe digital classification of Ancient Near Eastern cuneiform data,\u201d BAR Int. Ser., vol. 1075, pp. 65\u201370, 2002."},{"key":"2024110207213605445_j_itit-2023-0114_ref_036","unstructured":"S. Woolley, et al.., \u201cCommunicating cuneiform: the evolution of a multimedia cuneiform database,\u201d Visible Lang., vol. 36, pp. 308\u2013324, 2002."},{"key":"2024110207213605445_j_itit-2023-0114_ref_037","unstructured":"M. Jursa and R. Pirngruber, \u201cLaBaSi: Late Babylonian Signs,\u201d 2016. Available at: https:\/\/labasi.acdh.oeaw.ac.at\/ Accessed: Oct. 04, 2023."},{"key":"2024110207213605445_j_itit-2023-0114_ref_038","unstructured":"M. Jursa and R. Pirngruber, \u201cLaBaSi: Late Babylonian Signs. API,\u201d 2016. Available at: https:\/\/labasi.acdh.oeaw.ac.at\/data\/api Accessed: Oct. 04, 2023."},{"key":"2024110207213605445_j_itit-2023-0114_ref_039","unstructured":"R. Pirngruber, \u201cCuneiform palaeography in first millennium BC Babylonia,\u201d in Current Research in Cuneiform Palaeography: Proceedings of the Workshop Organized at the 64th Rencontre Assyriologique Internationale, Innsbruck 2018, E. Devecchi, J. Myn\u00e1\u0159ov\u00e1, and G. G. W. M\u00fcller, Eds., Gladbeck, PeWe-Verlag, 2019, pp. 157\u2013175."},{"key":"2024110207213605445_j_itit-2023-0114_ref_040","unstructured":"E. Jim\u00e9nez et al.., The \u201cElectronic Babylonian Library\u201d (eBL) Platform. 2018\u20132024. Available at: https:\/\/www.ebl.lmu.de\/ Accessed: Oct. 04, 2023."},{"key":"2024110207213605445_j_itit-2023-0114_ref_041","unstructured":"E. Jim\u00e9nez et al.., About in the \u201cElectronic Babylonian Library\u201d (eBL) Platform. 2018\u20132024. Available at: https:\/\/www.ebl.lmu.de\/about\/fragmentarium\/ Accessed: Oct. 04, 2023."},{"key":"2024110207213605445_j_itit-2023-0114_ref_042","doi-asserted-by":"crossref","unstructured":"C. Szegedy, et al.., \u201cGoing deeper with convolutions,\u201d in 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Boston, MA, USA, 2015, pp. 1\u20139.","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"2024110207213605445_j_itit-2023-0114_ref_043","doi-asserted-by":"crossref","unstructured":"K. He, et al.., \u201cDeep residual learning for image recognition,\u201d in 2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016, Las Vegas, NV, USA, June 27\u201330, 2016, IEEE Computer Society, 2016, pp.\u00a0770\u2013778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"2024110207213605445_j_itit-2023-0114_ref_047","doi-asserted-by":"crossref","unstructured":"J. Deng, W. Dong, R. Socher, L.-J. Li, Kai Li and Li Fei-Fei, \u201cImageNet: a large-scale hierarchical image database,\u201d in 2009 IEEE Conference on Computer Vision and Pattern Recognition Miami, FL, USA, 2009, pp. 248\u2013255.","DOI":"10.1109\/CVPR.2009.5206848"}],"container-title":["it - Information Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2023-0114\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2023-0114\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,2]],"date-time":"2024-11-02T07:22:07Z","timestamp":1730532127000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/itit-2023-0114\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,1]]},"references-count":44,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,10,30]]},"published-print":{"date-parts":[[2024,2,26]]}},"alternative-id":["10.1515\/itit-2023-0114"],"URL":"https:\/\/doi.org\/10.1515\/itit-2023-0114","relation":{},"ISSN":["1611-2776","2196-7032"],"issn-type":[{"value":"1611-2776","type":"print"},{"value":"2196-7032","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2,1]]}}}