发布时间：

2026-06-30

所属单位：

人工智能教育学部

论文名称：

A tree-BLSTM-based recognition system for online handwritten mathematical expressions

发表刊物：

Neural Computing and Applications

刊物所在地：

国内外公开发行

关键字：

Mathematical expression recognition; Tree-based BLSTM; Local CTC; Online handwriting

摘要：

Long short-term memory networks (LSTM) achieve great success in temporal dependency modeling for chain-structured data, such as texts and speeches. An extension toward more complex data structures as encountered in 2D graphic languages is proposed in this work. Specifically, we address the problem of handwritten mathematical expression recognition, using a tree-based BLSTM architecture allowing the direct labeling of nodes (symbol) and edges (relationship) from a graph modeling the input strokes. One major difference with the traditional approaches is that there is no explicit segmentation, recognition and layout extraction steps but a unique trainable system that produces directly a stroke label graph describing a mathematical expression. The proposed system, considering no grammar, achieves competitive results in online math expression recognition domain.

合写作者：

Mouchere, Harold,Viard-Gaudin, Christian

第一作者：

张婷

论文类型：

期刊论文

论文编号：

1570702627992375296

文献类型：

00001

卷号：

32

期号：

9

页面范围：

4689-4708

ISSN号：

0941-0643

是否译文：

否

发表时间：

2020-05-01

收录刊物：

其他（ESI、Scopus、OA）、EI、SCI