{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T01:54:33Z","timestamp":1769306073246,"version":"3.49.0"},"reference-count":33,"publisher":"Association for Computing Machinery (ACM)","issue":"1","funder":[{"DOI":"10.13039\/100019465","name":"Arab-German Young Academy of Sciences and Humanities","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100019465","id-type":"DOI","asserted-by":"crossref"}]},{"name":"German Federal Ministry of Education and Research"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["J. Comput. Cult. Herit."],"published-print":{"date-parts":[[2026,3,31]]},"abstract":"<jats:p>\n                    The deterioration of ancient inscriptions over centuries has resulted in irrevocable loss of vital written records, hampering epigraphic analysis, and creating significant gaps in historical knowledge. Factors such as eroded letters and physical damage often compromise the readability of these inscriptions. We present\n                    <jats:italic toggle=\"yes\">DeepHadad<\/jats:italic>\n                    , a neural network trained on procedurally generated synthetic data that use displacement maps and image-to-image translation to digitally restore severely damaged ancient inscriptions to a more readable state. The network\u2019s name is derived from the famous Panamuwa (I) inscription on the mid-8th century BCE Hadad statue, where, at certain places, only faint traces of letters remain on the damaged basalt statue. A key challenge in this work is the lack of well-preserved and damaged glyph pairs for training, as each glyph instance is unique and therefore not found in different states of erosion. We address this by generating synthetic training data through simulated erosion processes, enabling our neural network to successfully generalize to real data. By extracting and overlaying completion maps onto the 3D model, we significantly enhance the legibility of the barely recognizable Aramaic inscription on the Hadad statue. Quantitative and qualitative experiments confirm that our approach can recover textual content that would otherwise be lost or recoverable only through time-consuming manual work. This research opens a pioneering avenue for employing state-of-the-art AI to enrich the readability of ancient textual heritage. Our methodology facilitates a more comprehensive analysis of significant inscriptions and demonstrates the potential of AI-assistive technologies to advance the field of ancient restoration and epigraphic studies.\n                  <\/jats:p>","DOI":"10.1145\/3727623","type":"journal-article","created":{"date-parts":[[2025,4,2]],"date-time":"2025-04-02T16:46:53Z","timestamp":1743612413000},"page":"1-18","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["<i>DeepHadad<\/i>\n                    : Enhancing Readability of Damaged Inscriptions with Synthetic Data"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5547-9969","authenticated-orcid":false,"given":"Andrei C.","family":"Aioanei","sequence":"first","affiliation":[{"name":"Faculty of Theology and Religious Science, University of Strasbourg, Strasbourg, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6560-0988","authenticated-orcid":false,"given":"Jonathan","family":"Klein","sequence":"additional","affiliation":[{"name":"Computational Sciences Group, KAUST, Thuwal, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5927-3893","authenticated-orcid":false,"given":"Konstantin M.","family":"Klein","sequence":"additional","affiliation":[{"name":"Faculty of Humanities History, European Studies and Religious Studies, University of Amsterdam, Amsterdam, Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4244-5871","authenticated-orcid":false,"given":"Regine R.","family":"Hunziker-Rodewald","sequence":"additional","affiliation":[{"name":"Faculty of Theology and Religious Science, University of Strasbourg, Strasbourg, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1621-325X","authenticated-orcid":false,"given":"Dominik L.","family":"Michels","sequence":"additional","affiliation":[{"name":"Computational Sciences Group, KAUST, Thuwal, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,1,22]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0299297"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1668"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-022-04448-z"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/3491239"},{"key":"e_1_3_2_6_2","doi-asserted-by":"publisher","DOI":"10.3390\/rs14010006"},{"issue":"37","key":"e_1_3_2_7_2","doi-asserted-by":"crossref","first-page":"22743","DOI":"10.1073\/pnas.2003794117","article-title":"Restoration of fragmentary Babylonian texts using recurrent neural networks","volume":"117","author":"Fetaya Ethan","year":"2020","unstructured":"Ethan Fetaya, Yonatan Lifshitz, Elad Aaron, and Shai Gordin. 2020. Restoration of fragmentary Babylonian texts using recurrent neural networks. Proc. Natl. Acad. Sci. 117, 37 (2020), 22743\u201322751. Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:211990752","journal-title":"Proc. Natl. Acad. Sci"},{"key":"e_1_3_2_8_2","doi-asserted-by":"crossref","DOI":"10.1163\/9789004285101","volume-title":"A Cultural History of Aramaic: From the Beginnings to the Advent of Islam","author":"Gzella Holger","year":"2015","unstructured":"Holger Gzella. 2015. A Cultural History of Aramaic: From the Beginnings to the Advent of Islam. Brill, Leiden, Netherlands."},{"key":"e_1_3_2_9_2","doi-asserted-by":"publisher","DOI":"10.1145\/3459607"},{"key":"e_1_3_2_10_2","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He Kaiming","year":"2016","unstructured":"Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 770\u2013778. Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:206594692","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"e_1_3_2_11_2","doi-asserted-by":"publisher","unstructured":"Phillip Isola Jun-Yan Zhu Tinghui Zhou and Alexei A. Efros. 2017. Image-to-image translation with conditional adversarial networks. In 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 5967\u20135976. DOI: 10.1109\/CVPR.2017.632","DOI":"10.1109\/CVPR.2017.632"},{"key":"e_1_3_2_12_2","doi-asserted-by":"publisher","DOI":"10.3390\/heritage6050230"},{"key":"e_1_3_2_13_2","unstructured":"Diederik P. Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv:1412.6980. Retrieved from https:\/\/arxiv.org\/abs\/1412.6980"},{"key":"e_1_3_2_14_2","doi-asserted-by":"publisher","DOI":"10.1214\/11-EJS635"},{"key":"e_1_3_2_15_2","doi-asserted-by":"crossref","unstructured":"Chuan Li and Michael Wand. 2016. Precomputed real-time texture synthesis with Markovian generative adversarial networks. In European Conference on Computer Vision. Springer International Publishing Cham 702\u2013716.","DOI":"10.1007\/978-3-319-46487-9_43"},{"key":"e_1_3_2_16_2","doi-asserted-by":"publisher","DOI":"10.1145\/3469126"},{"key":"e_1_3_2_17_2","doi-asserted-by":"publisher","DOI":"10.3390\/rs13173499"},{"key":"e_1_3_2_18_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-86549-8_26"},{"key":"e_1_3_2_19_2","first-page":"57","volume-title":"In Remembrance of Me: Feasting with the Dead in the Ancient Middle East","author":"Niehr Herbert","year":"2014","unstructured":"Herbert Niehr. 2014. The Katumuwa stele in the context of Royal Mortuary cult at Samal. In In Remembrance of Me: Feasting with the Dead in the Ancient Middle East. Virginia Rimmer Herrmann and J. David Schloen (Eds.), Number 37 in Oriental Institute Museum Publications. The Oriental Institute of the University of Chicago, 57\u201362."},{"key":"e_1_3_2_20_2","first-page":"202","article-title":"Sam\u2019alian in its northwest semitic setting: A historical-comparative approach","volume":"81","author":"Noorlander Paul","year":"2012","unstructured":"Paul Noorlander. 2012. Sam\u2019alian in its northwest semitic setting: A historical-comparative approach. Orientalia 81 (Jan. 2012), 202\u2013238.","journal-title":"Orientalia"},{"key":"e_1_3_2_21_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2021.11.007"},{"key":"e_1_3_2_22_2","doi-asserted-by":"publisher","DOI":"10.5194\/isprs-annals-V-2-2020-989-2020"},{"key":"e_1_3_2_23_2","doi-asserted-by":"publisher","DOI":"10.1145\/3593431"},{"key":"e_1_3_2_24_2","doi-asserted-by":"publisher","unstructured":"Taesung Park Ming-Yu Liu Ting-Chun Wang and Jun-Yan Zhu. 2019. Semantic image synthesis with spatially-adaptive normalization. In 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2332\u20132341. DOI: 10.1109\/CVPR.2019.00244","DOI":"10.1109\/CVPR.2019.00244"},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1145\/3596711.3596772"},{"key":"e_1_3_2_26_2","doi-asserted-by":"crossref","unstructured":"Karl Van Eeden Risager Torkan Gholamalizadeh and Mostafa Mehdipour Ghazi. 2024. Non-Reference Quality Assessment for Medical Imaging: Application to Synthetic Brain MRIs. Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:271329036","DOI":"10.1007\/978-3-031-72744-3_19"},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_2_28_2","doi-asserted-by":"publisher","DOI":"10.1145\/3352631.3352632"},{"key":"e_1_3_2_29_2","unstructured":"SHINING 3D. 2019. EinScan Pro 2X Plus. Retrieved August 10 2024 from https:\/\/support.einscan.com\/en\/support\/solutions\/articles\/60001001468-user-manual-for-einscan-pro-and-einscan-pro-plus"},{"key":"e_1_3_2_30_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDAR.2003.1227801"},{"key":"e_1_3_2_31_2","doi-asserted-by":"publisher","unstructured":"Richard Szeliski Matthew Uyttendaele and Drew Steedly. 2011. Fast Poisson blending using multi-splines. In 2011 IEEE International Conference on Computational Photography (ICCP) 1\u20138. DOI: 10.1109\/ICCPHOT.2011.5753119","DOI":"10.1109\/ICCPHOT.2011.5753119"},{"key":"e_1_3_2_32_2","first-page":"5998","volume-title":"Advances in Neural Information Processing Systems","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. In Advances in Neural Information Processing Systems, 5998\u20136008. Retrieved from https:\/\/api.semanticscholar.org\/CorpusID:13756489"},{"key":"e_1_3_2_33_2","unstructured":"Ting-Chun Wang Ming-Yu Liu Jun-Yan Zhu Andrew Tao Jan Kautz and Bryan Catanzaro. 2018. High-resolution image synthesis and semantic manipulation with conditional GANs. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition."},{"key":"e_1_3_2_34_2","doi-asserted-by":"crossref","DOI":"10.1142\/12497","volume-title":"2D Computer Vision: Principles, Algorithms and Applications","author":"Zhang Yu-Jin","year":"2022","unstructured":"Yu-Jin Zhang. 2022. 2D Computer Vision: Principles, Algorithms and Applications. World Scientific Publishing, Singapore. Retrieved from https:\/\/www.worldscientific.com\/worldscibooks\/10.1142\/12497"}],"container-title":["Journal on Computing and Cultural Heritage"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3727623","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T14:21:07Z","timestamp":1769091667000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3727623"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,22]]},"references-count":33,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,3,31]]}},"alternative-id":["10.1145\/3727623"],"URL":"https:\/\/doi.org\/10.1145\/3727623","relation":{},"ISSN":["1556-4673","1556-4711"],"issn-type":[{"value":"1556-4673","type":"print"},{"value":"1556-4711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,22]]},"assertion":[{"value":"2024-05-17","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2024-12-09","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-01-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}