Fuentes Ferrer, RaúlDuque Domingo, JaimeHerrera Caro, Pedro Javier2025-04-242025-04-242025-03Raúl Fuentes-Ferrer, Jaime Duque-Domingo, Pedro Javier Herrera, Recognition of Egyptian hieroglyphic texts through focused generic segmentation and cross-validation voting, Applied Soft Computing, Volume 171, 2025, 112793, ISSN 1568-4946, https://doi.org/10.1016/j.asoc.2025.1127931568-4946 | eISSN 1872-9681https://doi.org/10.1016/j.asoc.2025.112793https://hdl.handle.net/20.500.14468/26492The registered version of this article, first published in “Applied Soft Computing, Volume 171, 2025", is available online at the publisher's website: Elsevier, https://doi.org/10.1016/j.asoc.2025.112793 La versión registrada de este artículo, publicado por primera vez en “Applied Soft Computing, Volume 171, 2025", está disponible en línea en el sitio web del editor: Elsevier, https://doi.org/10.1016/j.asoc.2025.112793Ancient Egyptian hieroglyphs form part of a complex language that has attracted the attention of Egyptologists, historians, and amateurs for centuries. In use for more than 3000 years, they consist of hundreds of symbols that can be transcribed into their Latin phonemes. Although there have been some previous works on the recognition of hieroglyphs through computer vision, this is a study of unprecedented depths and presents several unique contributions. On the one hand, we have created the largest and most complete dataset of existing Egyptian hieroglyphs to date, covering all the main symbols used on stelae. On the other, we have carried out a systematic analysis of detection, segmentation, and classification methods, focusing our research on a composite method of focused generic segmentation and classification with an ensemble model of ConvNeXt backbones using Cross-Validation Voting (CVV). Our trained model has been evaluated against several carved or painted stone stelae, obtaining excellent results. To the best of our knowledge, there is currently no other methodology capable of obtaining the classification results presented in this paper, and the method and the dataset presented represent a very significant advancement in the development of automated methods for reading Egyptian hieroglyphic texts.eninfo:eu-repo/semantics/embargoedAccess1203.17 Informáticaartículoegyptian hieroglyphsgeneric segmentationSAMCVVConvNeXt