@InProceedings{PauRiba2017,
author="Pau Riba
and Anjan Dutta
and Josep Llados
and Alicia Fornes",
title="Graph-based deep learning for graphics classification",
booktitle="14th International Conference on Document Analysis and Recognition",
year="2017",
pages="29--30",
abstract="Graph-based representations are a common way to deal with graphics recognition problems. However, previous works were mainly focused on developing learning-free techniques. The success of deep  learning frameworks have proved that learning is a powerful tool to solve many problems, however it is not straightforward to extend these methodologies to non euclidean data such as graphs. On the other hand, graphs are a good representational structure for graphical entities. In this work, we present some deep learning techniques that have been proposed in the literature for graph-based representations andwe show how they can be used in graphics recognition problems",
optnote="DAG; 600.097; 601.302; 600.121",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=3058), last updated on Fri, 06 Sep 2024 12:52:31 +0200",
doi="10.1109/ICDAR.2017.262",
file=":http://refbase.cvc.uab.es/files/RDL2017b.pdf:PDF"
}