Tree-based BLSTM for mathematical expression recognition

International audienceIn this study, we extend the chain-structuredBLSTM to tree structure topology and apply this new networkmodel for online math expression recognition. The proposedsystem addresses the recognition task as a graph buildingproblem. The input expression is a sequence of strokes fromwhich an intermediate graph is derived using temporal andspatial relations among strokes. In this graph, a node correspondsto a stroke and an edge denotes the relationship between a pairof strokes. Then several trees are derived from the graph andlabeled with Tree-based BLSTM. The last step is to merge theselabeled trees to build an admissible label graph (LG) modeling 2-D formulas uniquely. The proposed system achieves competitiveresults in online math expression recognition domain