Torres Aguilar, S. O., & Jolivet, V. (In press). Handwritten Text Recognition for Documentary Medieval Manuscripts. Journal of Data Mining and Digital Humanities.
Peer Reviewed verified by ORBi
Torres Aguilar, S. O., & Jolivet, V. (2023). Handwritten Text Recognition for Documentary Medieval Manuscripts. Journal of Data Mining and Digital Humanities. doi:10.46298/jdmdh.10484
Peer Reviewed verified by ORBi
Claustre, J., Smith, D., & TORRES AGUILAR, S. O. (2023). The e-NDP project : collaborative digital edition of the Chapter registers of Notre-Dame of Paris (1326-1504). Ground-truth for handwriting text recognition (HTR) on late medieval manuscripts. Zenodo. doi:10.5281/zenodo.7575693
The e-NDP project, funded by the ANR, is led by the LaMOP (Julie Claustre and Darwin Smith). The...
TORRES AGUILAR, S. O., & Jolivet, V. (2023). HTR model for Latin and French Medieval Documentary Manuscripts (12th-15th). doi:10.5281/zenodo.7547438
This HTR model operates in a multilingual environment (Latin and Old French) and it is able to re...
Torres Aguilar, S. O., & Jolivet, V. (2022). HTR fine tuning for medieval manuscripts models: strategies and evaluation [Paper presentation]. Documents anciens et reconnaissance automatique des écritures manuscrites, Paris, France.
Torres Aguilar, S. O., & Claustre, J. (2022). Le projet e-NDP, Notre Dame de Paris et son cloître [Paper presentation]. Intelligence artificielle et Société, Paris, France.
Torres Aguilar, S. O. (2022). Multilingual Named Entity Recognition for Medieval Charters using Stacked Embeddings and BERT-based Models. In Second Workshop on Language Technologies for Historical and Ancient Languages (LT4HALA, 2022).
Peer reviewed
Jolivet, V., & TORRES AGUILAR, S. O. (2022). Document similarity and topic clues. A historiographical study case [Paper presentation]. Digital Humanities 2022 Conference, Tokyo, Japan.
Peer reviewed
Torres Aguilar, S. O., Chastang, P., & Tannier, X. (2022). Automatic medieval charters structure detection : A Bi-LSTM linear segmentation approach. Journal of Data Mining and Digital Humanities, 2022. doi:10.46298/jdmdh.8646
Peer reviewed
Chastang, P., TORRES AGUILAR, S. O., & Tannier, X. (2021). A Named Entity Recognition Model for Medieval Latin Charters. Digital Humanities Quarterly, 15 (4).
Peer Reviewed verified by ORBi
Stutzmann, D., Torres Aguilar, S. O., & Chaffenet, P. (2021). HOME-Alcar: Aligned and Annotated Cartularies. doi:10.5281/zenodo.5600884
Torres Aguilar, S. O., & Stutzmann, D. (2021). Named Entity Recognition for French medieval charters. In Workshop on Natural Language Processing for Digital Humanities.
Peer reviewed
Torres Aguilar, S. O. (2019). Un modèle de reconnaissance automatique des entités nommées et des structures textuelles pour les corpus diplomatiques médiolatins [Doctoral thesis, Université Paris-Saclay]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/54749
Torres Aguilar, S. O. (2017). La reconnaissance des entités nommées dans les bases numériques de chartes médiévales en latin : le cas du Corpus Burgundiae Medii Aevi (xe-xiiie siècle). Medievales, 73. doi:10.4000/medievales.8182
Peer reviewed
Torres Aguilar, S. O., Tannier, X., & Chastang, P. (2016). Named entity recognition applied on a data base of Medieval Latin charters. The case of chartae burgundiae. In 3rd International Workshop on Computational History (HistoInformatics 2016).
Peer reviewed