Downloads provided by UsageCounts
The ICFHR2016 Competition on the Classification of Medieval Handwritings in Latin Script (CLaMM), jointly organized by Computer Scientists and Humanists (paleographers) provided a rich database of European medieval manuscripts to the community on Handwriting Analysis and Recognition. If you use this dataset, please cite: Florence Cloppet, Véronique Eglin, Van Cuong Kieu, Dominique Stutzmann, and Nicole Vincent, "ICFHR2016 Competition on the Classification of Medieval Handwritings in Latin Script", Proceedings of International Conference on Frontiers in Handwriting Recognition, Los Alamos : IEEE, 2016, p. 590-595. [https://doi.org/10.1109/ICFHR.2016.0113] At this competition, we proposed two independent classification tasks which attracted five participants with seven submitted classifiers. Those classifiers are trained on a set of 2000 images with their ground truths. In the first task of script crisp classification, the classifiers have been evaluated on a test set of 1000 single-type manuscripts. In the second task of “Fuzzy Classification”, the classifiers have been carried out on a set of 2000 multi-script-type manuscripts. The present dataset contains the training dataset, both test datasets (task 1 and task 2) and the matrices provided by the competitors. It was first published on a https://clamm.irht.cnrs.fr/icfhr2016-clamm/ in Oct. 2016.
{"references": ["Florence Cloppet, V\u00e9ronique Eglin, Van Cuong Kieu, Dominique Stutzmann, and Nicole Vincent, \"ICFHR2016 Competition on the Classification of Medieval Handwritings in Latin Script\", Proceedings of International Conference on Frontiers in Handwriting Recognition, Los Alamos : IEEE, 2016, p. 590-595. https://doi.org/10.1109/ICFHR.2016.0113"]}
latin palaeography, image analysis, script classification
latin palaeography, image analysis, script classification
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 13 | |
| downloads | 3 |

Views provided by UsageCounts
Downloads provided by UsageCounts