Resources

Additional references:

Mike Kestemont, Vincent Christlein, and Dominique Stutzmann, “Artificial Paleography: Computational Approaches to Identifying Script Types in Medieval Manuscripts,” in Speculum 92, no S1 (octobre 2017): pp. 86-109. https://doi.org/10.1086/694112

Christopher Tensmeyer, Daniel Saunders, and Tony Martinez, “Convolutional Neural Networks for Font Classification,” in 14th IAPR International Conference on Document Analysis and Recognition. ICDAR 2017, Kyoto, 2017, pp. 985-990. https://doi.org/10.1109/ICDAR.2017.164

Vincent Christlein, Martin Gropp, Stefan Fiel, Andreas Maier, “Unsupervised Feature Learning for Writer Identification and Writer Retrieval,” in 14th IAPR International Conference on Document Analysis and Recognition. ICDAR 2017, Kyoto, 2017, pp. 991-997. https://doi.org/10.1109/ICDAR.2017.165

Additional resources:
Annotation of foreground/background, noise and script type on ICFHR2016 CLaMM Training Dataset by C. Tensmeyer (art. cit. supra), available for download at http://axon.cs.byu.edu/clamm

Open source code for script classification and dating
V. Christlein, ICFHR2016 code: https://github.com/VChristlein/clamm-icfhr16/
V. Christlein, ICDAR2017 code: https://github.com/VChristlein/icdar17code
M. Kestemont, ICFHR2016 code: https://github.com/mikekestemont/DeepScript
M. Kestemont, ICDAR2017 code: https://github.com/mikekestemont/DeepFAU
C. Tensmeyer, ICFHR2016 code: https://github.com/ctensmeyer/clamm_submission
C. Tensmeyer, ICDAR2017 code: https://github.com/ctensmeyer/clamm_2017

Raw outputs of candidates