Results 1 to 10 of about 30 (30)

Generic HTR Models for Medieval Manuscripts. The CREMMALab Project [PDF]

Journal of Data Mining and Digital Humanities, 2023
In the Humanities, the emergence of digital methods has opened up research questions to quantitative analysis. This is why HTR technology is increasingly involved in humanities research projects following precursors such as the Himanis project.
Ariane Pinche
doaj   +1 more source

Handwritten Text Recognition for Documentary Medieval Manuscripts [PDF]

Journal of Data Mining and Digital Humanities, 2023
Handwritten Text Recognition (HTR) techniques aim to accurately recognize sequences of characters in input manuscript images by training artificial intelligence models to capture historical writing features.
Sergio Torres Aguilar, Vincent Jolivet
doaj   +1 more source

Ground-truth Free Evaluation of HTR on Old French and Latin Medieval Literary Manuscripts. [PDF]

, 2022
As more and more projects openly release ground truth for handwritten text recognition (HTR), we expect the quality of automatic transcription to improve on unseen data. Getting models robust to scribal and material changes is a necessary step for specific data mining tasks. However, evaluation of HTR results requires ground truth to compare prediction
openaire   +1 more source

Understanding the application of handwritten text recognition technology in heritage contexts: a systematic review of Transkribus in published research. [PDF]

Arch Sci (Dordr), 2022
Nockels J, Gooding P, Ames S, Terras M.
europepmc   +1 more source

Abstracts from the 53rd European Society of Human Genetics (ESHG) Conference: Interactive e-Posters. [PDF]

Eur J Hum Genet, 2020
europepmc   +1 more source

iForal: Automated Handwritten Text Transcription for Historical Medieval Manuscripts. [PDF]

J Imaging
Matos A, Almeida P, Correia PL, Pacheco O.   +3 more
europepmc   +1 more source

Advancements and Challenges in Handwritten Text Recognition: A Comprehensive Survey. [PDF]

J Imaging
AlKendi W, Gechter F, Heyberger L, Guyeux C.   +3 more
europepmc   +1 more source

The artificial intelligence cooperative: READ-COOP, Transkribus, and the benefits of shared community infrastructure for automated text recognition. [PDF]

Open Res Eur
Terras M, Anzinger B, Gooding P, Mühlberger G, Prien M, Nockels J, Romein CA, Stauder A, Stauder F.   +8 more
europepmc   +1 more source

Historical Text Line Segmentation Using Deep Learning Algorithms: Mask-RCNN against U-Net Networks. [PDF]

J Imaging
Fizaine FC, Bard P, Paindavoine M, Robin C, Bouyé E, Lefèvre R, Vinter A.   +6 more
europepmc   +1 more source

Handling Heavily Abbreviated Manuscripts: HTR Engines vs Text Normalisation Approaches

Lecture Notes in Computer Science, 2021
Jean-Baptiste Camps, Chahan Vidal-Gorène   +1 more
exaly