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This paper presents a Convolutional Neural Network (CNN) based page segmentation method for handwritten historical document images.
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M. Bulacu, R. van Koert, L. Schomaker, and T. van der Zant, “Layout analysis of handwritten historical documents for searching the archive of the cabinet of the dutch queen,” in Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) , vol. 1. IEEE, 2007, pp. 357–361
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T. Van Phan, B. Zhu, and M. Nakagawa, “Development of nom character segmentation for collecting patterns from historical document pages,” in Proceedings of the 2011 Workshop on Historical Document Imaging and Processing . ACM, 2011, pp. 133–139
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T. Wang, D. J. Wu, A. Coates, and A. Y. Ng, “End-to-end text recognition with convolutional neural networks,” in Pattern Recognition (ICPR), 2012 21st International Conference on . IEEE, 2012, pp. 3304–3308
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C. Panichkriangkrai, L. Li, and K. Hachimura, “Character segmentation and retrieval for learning support system of japanese historical books,” in Proceedings of the 2nd International Workshop on Historical Document Imaging and Processing . ACM, 2013, pp. 118–122
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R. Cohen, A. Asi, K. Kedem, J. El-Sana, and I. Dinstein, “Robust text and drawing segmentation algorithm for historical documents,” in Proceedings of the 2nd International Workshop on Historical Document Imaging and Processing . ACM, 2013, pp. 110–117
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K. Chen, M. Seuret, M. Liwicki, J. Hennebert, and R. Ingold, “Page segmentation of historical document images with convolutional autoencoders,” in Document Analysis and Recognition (ICDAR), 2015 13th International Conference on . IEEE, 2015, pp. 1011–1015
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2013
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K. Chen, H. Wei, M. Liwicki, J. Hennebert, and R. Ingold, “Robust text line segmentation for historical manuscript images using color and texture,” in 2014 22nd International Conference on Pattern Recognition (ICPR) . IEEE, 2014, pp. 2978–2983
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K. Chen, H. Wei, J. Hennebert, R. Ingold, and M. Liwicki, “Page segmentation for historical handwritten document images using color and texture features,” in Frontiers in Handwriting Recognition (ICFHR), 2014 14th International Conference on . IEEE, 2014, pp. 488–493
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B. Gatos, G. Louloudis, and N. Stamatopoulos, “Segmentation of historical handwritten documents into text zones and text lines,” in Frontiers in Handwriting Recognition (ICFHR), 2014 14th International Conference on . IEEE, 2014, pp. 464–469
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A. Asi, R. Cohen, K. Kedem, J. El-Sana, and I. Dinstein, “A coarse-to-fine approach for layout analysis of ancient manuscripts,” in Frontiers in Handwriting Recognition (ICFHR), 2014 14th International Conference on . IEEE, 2014, pp. 140–145
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K. Chen, M. Seuret, H. Wei, M. Liwicki, J. Hennebert, and R. Ingold, “Ground truth model, tool, and dataset for layout analysis of historical documents,” in IS&T/SPIE Electronic Imaging . International Society for Optics and Photonics, 2015, pp. 940 204–940 204
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J. Long, E. Shelhamer, and T. Darrell, “Fully convolutional networks for semantic segmentation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2015, pp. 3431–3440
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K. Chen, C.-L. Liu, M. Seuret, M. Liwicki, J. Hennebert, and R. Ingold, “Page segmentation for historical document images based on superpixel classification with unsupervised feature learning,” in Document Analysis System (DAS), 2016 12th IAPR International Workshop on . IEEE, 2016, pp. 299–304
2016
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K. Chen, M. Seuret, M. Liwicki, J. Hennebert, C.-L. Liu, and R. Ingold, “Page segmentation for historical handwritten document images using conditional random fields,” in Frontiers in Handwriting Recognition (ICFHR), 2016 15th International Conference on . IEEE, 2016, pp. 90–95
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K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2016, pp. 770–778
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F. Simistira, M. Seuret, N. Eichenberger, A. Garz, M. Liwicki, and R. Ingold, “Diva-hisdb: A precisely annotated large dataset of challenging medieval manuscripts,” in Frontiers in Handwriting Recognition (ICFHR), 2016 15th International Conference on . IEEE, 2016, pp. 471–476
2016
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