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Author Pau Riba; Anjan Dutta; Josep Llados; Alicia Fornes
Title Graph-based deep learning for graphics classification Type Conference Article
Year 2017 Publication 12th IAPR International Workshop on Graphics Recognition Abbreviated Journal
Volume Issue Pages 29-30
Abstract (down) 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
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
Area Expedition Conference GREC
Notes DAG; 600.097; 601.302; 600.121 Approved no
Call Number Admin @ si @ RDL2017b Serial 3058
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