{"ID":2833525,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.03817","arxiv_id":"2512.03817","title":"HieroGlyphTranslator: Automatic Recognition and Translation of Egyptian Hieroglyphs to English","abstract":"Egyptian hieroglyphs, the ancient Egyptian writing system, are composed entirely of drawings. Translating these glyphs into English poses various challenges, including the fact that a single glyph can have multiple meanings. Deep learning translation applications are evolving rapidly, producing remarkable results that significantly impact our lives. In this research, we propose a method for the automatic recognition and translation of ancient Egyptian hieroglyphs from images to English. This study utilized two datasets for classification and translation: the Morris Franken dataset and the EgyptianTranslation dataset. Our approach is divided into three stages: segmentation (using Contour and Detectron2), mapping symbols to Gardiner codes, and translation (using the CNN model). The model achieved a BLEU score of 42.2, a significant result compared to previous research.","short_abstract":"Egyptian hieroglyphs, the ancient Egyptian writing system, are composed entirely of drawings. Translating these glyphs into English poses various challenges, including the fact that a single glyph can have multiple meanings. Deep learning translation applications are evolving rapidly, producing remarkable results that...","url_abs":"https://arxiv.org/abs/2512.03817","url_pdf":"https://arxiv.org/pdf/2512.03817v1","authors":"[\"Ahmed Nasser\",\"Marwan Mohamed\",\"Alaa Sherif\",\"Basmala Mahmoud\",\"Shereen Yehia\",\"Asmaa Saad\",\"Mariam S. El-Rahmany\",\"Ensaf H. Mohamed\"]","published":"2025-12-03T14:05:18Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.LG\"]","methods":"[\"Convolutional Neural Network\"]","has_code":false}