Tree-based BLSTM for mathematical expression recognition

Abstract : In this study, we extend the chain-structured BLSTM to tree structure topology and apply this new network model for online math expression recognition. The proposed system addresses the recognition task as a graph building problem. The input expression is a sequence of strokes from which an intermediate graph is derived using temporal and spatial relations among strokes. In this graph, a node corresponds to a stroke and an edge denotes the relationship between a pair of strokes. Then several trees are derived from the graph and labeled with Tree-based BLSTM. The last step is to merge these labeled trees to build an admissible label graph (LG) modeling 2-D formulas uniquely. The proposed system achieves competitive results in online math expression recognition domain.
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Communication dans un congrès
International Conference on Document Analysis and Recognition (ICDAR), Nov 2017, Kyoto, Japan. 2017, Proceeding of International Conference on Document Analysis and Recognition. 〈http://u-pat.org/ICDAR2017/index.php〉. 〈10.1109/ICDAR.2017.154〉
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Soumis le : mardi 5 décembre 2017 - 16:32:28
Dernière modification le : jeudi 19 avril 2018 - 11:46:05

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Ting Zhang, Harold Mouchère, Christian Viard-Gaudin. Tree-based BLSTM for mathematical expression recognition. International Conference on Document Analysis and Recognition (ICDAR), Nov 2017, Kyoto, Japan. 2017, Proceeding of International Conference on Document Analysis and Recognition. 〈http://u-pat.org/ICDAR2017/index.php〉. 〈10.1109/ICDAR.2017.154〉. 〈hal-01576305〉

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