List of scientific publications where DocCreactor has been used
List of scientific publications where DocCreactor has been used
Pack, C., Liu, Y., Soh, L. K., & Lorang, E. (2022). Augmentation-based Pseudo-Groundtruth Generation for Deep Learning in Historical Document Segmentation for Greater Levels of Archival Description and Access. ACM Journal on Computing and Cultural Heritage.
Vögtlin, L., Maergner, P., & Ingold, R. (2022). DIVA-DAF: A Deep Learning Framework for Historical Document Image Analysis. arXiv preprint arXiv:2201.08295.
Camps, J. B., & Couffignal, G. G. (2017). La production de corpus d’occitan médiéval et prémoderne: problèmes et perspectives de travail. Actes du XII\ieme {} Congrès International de l’Association Internatioale d’Études Occitanes, Albi, 2017.
Hamdi, A., Pontes, E. L., Sidere, N., Coustaty, M., & Doucet, A. (2022). In-depth analysis of the impact of OCR errors on named entity recognition and linking. Natural Language Engineering, 1-24.
Bui, Q. A., Mollard, D., & Tabbone, S. (2019, September). Automatic synthetic document image generation using generative adversarial networks: application in mobile-captured document analysis. In 2019 International Conference on Document Analysis and Recognition (ICDAR) (pp. 393-400). IEEE.
Huynh, V. N., Hamdi, A., & Doucet, A. (2020, November). When to Use OCR Post-correction for Named Entity Recognition?. In International Conference on Asian Digital Libraries (pp. 33-42). Springer, Cham.
Nguyen, N. K., Boroş, E., Lejeune, G., & Doucet, A. (2020, November). Impact analysis of document digitization on event extraction. In 4th workshop on natural language for artificial intelligence (NL4AI 2020) co-located with the 19th international conference of the Italian Association for artificial intelligence (AI* IA 2020) (Vol. 2735, pp. 17-28).
Linhares Pontes, E., Hamdi, A., Sidere, N., & Doucet, A. (2019, November). Impact of OCR quality on named entity linking. In International Conference on Asian Digital Libraries (pp. 102-115). Springer, Cham.
Hamdi, A., Jean-Caurant, A., Sidere, N., Coustaty, M., & Doucet, A. (2019, June). An Analysis of the Performance of Named Entity Recognition over OCRed Documents. In 2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL) (pp. 333-334). IEEE.
Karpinski, R., & Belaïd, A. (2018, December). Combination of Two Fully Convolutional Neural Networks for Robust Binarization. In Asian Conference on Computer Vision (pp. 509-524). Springer, Cham.
Choi, K. Y., Coüasnon, B., Ricquebourg, Y., & Zanibbi, R. (2018). Music Symbol Detection with Faster R-CNN Using Synthetic Annotations.
Choi, K. Y., Coüasnon, B., Ricquebourg, Y., & Zanibbi, R. (2018). Music Symbol Detection with Faster R-CNN Using Synthetic Annotations.
Camps, J. B., & Couffignal, G. G. (2017, July). La production de corpus d'occitan médiéval et prémoderne. In Actes du XIIe Congrès de l’Association internationale d’études occitanes Albi, 2017
Liu, N., Zhang, D., Xu, X., Liu, W., Ke, D., Guo, L., ... Chen, L. (2017, November). An Iterative Refinement Framework for Image Document Binarization with Bhattacharyya Similarity Measure. In Document Analysis and Recognition (ICDAR), 2017 14th IAPR International Conference on (Vol. 1, pp. 93-98). IEEE.
Roy, P. P., Bhunia, A. K., & Pal, U. (2017). HMM-based writer identification in music score documents without staff-line removal. Expert Systems with Applications, 89, 222-240. Julca-Aguilar, F. D., \& Hirata, N. S. (2017). Image operator learning coupled with CNN classification and its application to staff line removal. arXiv preprint arXiv:1709.06476.
Calvo-Zaragoza, J., Pertusa, A., & Oncina, J. (2017). Staff-line detection and removal using a convolutional neural network. Machine Vision and Applications, 28(5-6), 665-674.
Garg, R., & Chaudhury, S. (2016, April). Automatic Selection of Parameters for Document Image Enhancement Using Image Quality Assessment. In Document Analysis Systems (DAS), 2016 12th IAPR Workshop on (pp. 422-427). IEEE.
Montagner, I. S., Hirata, N. S., Hirata, R., & Canu, S. (2016, September). NILC: a two level learning algorithm with operator selection. In Image Processing (ICIP), 2016 IEEE International Conference on (pp. 1873-1877). IEEE.
Montagner, I. S., Hirata, R., Hirata, N. S., & Canu, S. (2016, October). Kernel approximations for W-operator learning. In Graphics, Patterns and Images (SIBGRAPI), 2016 29th SIBGRAPI Conference on (pp. 386-393). IEEE.
Montagner, I. S., Hirata, N. S., & Hirata, R. (2016, October). Image operator learning and applications. In Graphics, Patterns and Images Tutorials (SIBGRAPI-T), SIBGRAPI Conference on (pp. 38-50). IEEE.
Baro, A., Riba, P., & Fornés, A. (2016, October). Towards the recognition of compound music notes in handwritten music scores. In 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) (pp. 465-470). IEEE.
Pastor-Pellicer, J., Garz, A., Ingold, R., & Castro-Bleda, M. J. (2015, August). Combining Learned Script Points and Combinatorial Optimization for Text Line Extraction. In Proceedings of the 3rd International Workshop on Historical Document Imaging and Processing (pp. 71-78). ACM.
Lagarrigue, M., Rossant, F., Pierrot, A., Gardes, J., Maldivi, C., & Petit, E. (2014, November). Assessing the quality of digital re-publishing of textual documents through the follow-up of a correction protocol by crowdsourcing. In Computational Intelligence for Multimedia Understanding (IWCIM), 2014 International Workshop on (pp. 1-5). IEEE.
Rabaev, I., Dinstein, I., El-Sana, J., & Kedem, K. (2014, October). Segmentation-free keyword retrieval in historical document images. In International Conference Image Analysis and Recognition (pp. 369-378). Springer, Cham.
dos Santos Montagner, I., Hirata, R., & Hirata, N. S. (2014, August). A machine learning based method for staff removal. In 2014 22nd International Conference on Pattern Recognition (ICPR) (pp. 3162-3167). IEEE.
Montagner, I. S., Hirata, R., & Hirata, N. S. (2014, October). Learning to remove staff lines from music score images. In Image Processing (ICIP), 2014 IEEE International Conference on (pp. 2614-2618). IEEE.
Géraud, T. (2014, October). A morphological method for music score staff removal. In Image Processing (ICIP), 2014 IEEE International Conference on (pp. 2599-2603). IEEE.
Fischer, A., Visani, M., Kieu, V. C., & Suen, C. Y. (2013, August). Generation of learning samples for historical handwriting recognition using image degradation. In Proceedings of the 2nd International Workshop on Historical Document Imaging and Processing (pp. 73-79). ACM.