Graph-Based Deep Learning for Graphics Classification
Riba, P; Dutta, A; Llados, J; et al.Fornes, A
Date: 29 January 2018
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publisher DOI
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 ...
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.
Computer Science
Faculty of Environment, Science and Economy
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