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Graph-based deep learning for graphics classification
Pau Riba, Anjan Dutta, Josep Llados and Alicia Fornes. 2017. Graph-based deep learning for graphics classification. 12th IAPR International Workshop on Graphics Recognition.29–30.
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 and
we show how they can be used in graphics recognition problems
Graph-based deep learning for graphics classificationPau RibaAnjan DuttaJosep LladosAlicia Fornesopenurl:?ctx_ver=Z39.88-2004&rfr_id=info%3Asid%2Frefbase.cvc.uab.es%2F&genre=proceeding&title=Graph-based%20deep%20learning%20for%20graphics%20classification&date=2017&spage=29&epage=30&aulast=Pau%20Riba&au=Anjan%20Dutta&au=Josep%20Llados&au=Alicia%20Fornes&sid=refbase%3ACVCPau Riba, Anjan Dutta, Josep Llados and Alicia Fornes. 2017. Graph-based deep learning for graphics classification. 12th IAPR International Workshop on Graphics Recognition.29-30.2017ConferencePapertextfile:http://refbase.cvc.uab.es/files/RDL2017b.pdf12th IAPR International Workshop on Graphics Recognition20172930