Tree-based BLSTM for mathematical expression recognition
Résumé
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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