![]() The area around Djoser’s Step Pyramid complex comes immediately alive for the visitor (Screenshot) The team is constantly working on adding new sites to visit with the tomb of Horemheb (KV 57) as the latest addition. Visitors to Describing Egypt can choose from various sites such as royal tombs of the New Kingdom to tombs of Old Kingdom private officials and several temples from later periods. With a focus on describing the sites around the country “through Egyptian Eyes”, they have partnered with the wonderful resources of (see below) as well as the to add important contextual information to their virtual tours. is a project which begun in 2012 as the work of motion designer Salma el-Dardiry and developer Karim Mansour. Neurocomputing 414: 67-75.Virtual tours to archaeological sites and museums with Egyptian collections have been on our mind for a long time. A holistic representation guided attention network for scene text recognition. Proceedings of the European Conference on Computer Vision (ECCV), 367-383. Start, follow, read: End-to-end full-page handwriting recognition. Wigington, C., Tensmeyer, C., Davis, B., Barrett, W., Price, B. IEEE (ed.), 2019 International Conference on Document Analysis and Recognition Workshops (ICDARW) 5: 35-40. JSESH TEXTS FULLA computationally efficient pipeline approach to full page offline handwritten text recognition. Journal of Language Modelling 5/1: 131-163.Ĭhung, J. A probabilistic model of ancient Egyptian writing. Digital Scholarship in the Humanities 32 (suppl. Analyzing and visualizing ancient Maya hieroglyphics using shape: From computer vision to Digital Humanities. Alcalá de Henares: Universidad de Alcalá. Handbook of digital Egyptology: Texts(Monografías de Oriente Antiguo 1). Lieja: Presses Universitaires de Liège, 139-155. Winand (eds.), Texts, languages and information technology in Egyptology (Aegyptiaca Leodiensia 9). Oxford / Londres: Griffith Institute / Oxford University Press. Being an introduction to the study of hieroglyphs. IEEE/ACM Transactions on Audio, Speech, and Language Processing 99 (doi 10.1109/TASLP.2016.2547743). Combination of Language Models for Word Prediction: An Exponential Approach. (doi 10.5772/61753)Ĭruz Cavalieri D., Palazuelos-Cagigas S., Bastos-Filho T., Sarcinelli-Filho, M. International Journal of Advanced Robotic Systems 12/170: 1-14. On Combining Language Models to Improve a Text-based Human-machine Interface. “Manuel de Codage”: A standard system for the computer-encoding of Egyptian transliteration and hieroglyphic textsĬruz Cavalieri D., Bastos-Filho T., Palazuelos-Cagigas S., Sarcinelli-Filho, M. & Argenti, F., A Deep Learning Approach to Ancient Egyptian Hieroglyphs Classification, IEEE Acesss 9 (2021), 1-10. This will allow the researchers to interactively check the chosen corpus without manually encoding much of the text at the sentence level.īarucci, A., Cucci, C., Franci, M., Loschiavo, M. The project will try techniques for segmentation of the hieroglyphic script in these texts and classification systems based on deep neural networks. JSESH TEXTS MANUALThe OCR-PT-CT project will propose an OCR system adapted to the chosen corpus that will permit to keep manual encoding at a minimum. Thanks to its interdisciplinary team (Egyptology and Engineering), the OCR-PT-CT project will implement a task sequence that will constantly consider the flexibility and range of the data set regarding its possible usability with different complex writing systems. Access to these editions has been granted by the Oriental Institute (University of Chicago) and James P. From March to December 2022, the OCR-PT-CT project (PIUAH21/AH-036), funded by Universidad de Alcalá and in synergy with the MORTEXVAR project (Comunidad de Madrid) and the GEINTRA and CIARQ research groups, will assure the quality of input data by using the text editions of current reference in Egyptological research. ![]()
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