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Authors: Adeline Granet ; Emmanuel Morin ; Harold Mouchère ; Solen Quiniou and Christian Viard-Gaudin

Affiliation: Université de Nantes, France

Keyword(s): Handwriting Recognition, Historical Document, Transfer Learning, Deep Neural Network, Unlabeled Data.

Related Ontology Subjects/Areas/Topics: Applications ; Cardiovascular Imaging and Cardiography ; Cardiovascular Technologies ; Computer Vision, Visualization and Computer Graphics ; Health Engineering and Technology Applications ; Image Understanding ; Pattern Recognition ; Signal Processing ; Software Engineering

Abstract: In this work, we investigate handwriting recognition on new historical handwritten documents using transfer learning. Establishing a manual ground-truth of a new collection of handwritten documents is time consuming but needed to train and to test recognition systems. We want to implement a recognition system without performing this annotation step. Our research deals with transfer learning from heterogeneous datasets with a ground-truth and sharing common properties with a new dataset that has no ground-truth. The main difficulties of transfer learning lie in changes in the writing style, the vocabulary, and the named entities over centuries and datasets. In our experiment, we show how a CNN-BLSTM-CTC neural network behaves, for the task of transcribing handwritten titles of plays of the Italian Comedy, when trained on combinations of various datasets such as RIMES, Georges Washington, and Los Esposalles. We show that the choice of the training datasets and the merging methods are d eterminant to the results of the transfer learning task. (More)

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Paper citation in several formats:
Granet, A.; Morin, E.; Mouchère, H.; Quiniou, S. and Viard-Gaudin, C. (2018). Transfer Learning for Handwriting Recognition on Historical Documents. In Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-276-9; ISSN 2184-4313, SciTePress, pages 432-439. DOI: 10.5220/0006598804320439

@conference{icpram18,
author={Adeline Granet. and Emmanuel Morin. and Harold Mouchère. and Solen Quiniou. and Christian Viard{-}Gaudin.},
title={Transfer Learning for Handwriting Recognition on Historical Documents},
booktitle={Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2018},
pages={432-439},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006598804320439},
isbn={978-989-758-276-9},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Transfer Learning for Handwriting Recognition on Historical Documents
SN - 978-989-758-276-9
IS - 2184-4313
AU - Granet, A.
AU - Morin, E.
AU - Mouchère, H.
AU - Quiniou, S.
AU - Viard-Gaudin, C.
PY - 2018
SP - 432
EP - 439
DO - 10.5220/0006598804320439
PB - SciTePress