Tree-Based BLSTM for Mathematical Expression Recognition
Ting Zhang, Harold Mouchère, Christian Viard-Gaudin · 2017
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.