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Stroke-Based Stochastic Context-Free Grammar for On-line Handwritten Mathematical Expression Recognition
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This article is published in Technical report of IEICE. Thought and language.The article was published on 2006-02-17 and is currently open access. It has received 18 citations till now. The article focuses on the topics: Stochastic grammar & Stochastic context-free grammar.read more
Citations
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Journal ArticleDOI
Recognition of on-line handwritten mathematical expressions using 2D stochastic context-free grammars and hidden Markov models
TL;DR: In this article, a formal model for the recognition of on-line handwritten mathematical expressions using 2D stochastic context-free grammars and hidden Markov models is described.
Journal ArticleDOI
Track, Attend, and Parse (TAP): An End-to-End Framework for Online Handwritten Mathematical Expression Recognition
Jianshu Zhang,Jun Du,Lirong Dai +2 more
TL;DR: The proposed end-to-end framework does not require the explicit symbol segmentation and a predefined expression grammar for parsing and demonstrates the strong complementarity between offline information with static-image input and online information with ink-trajectory input by blending a fully convolutional networks-based watcher into TAP.
Journal ArticleDOI
A global learning approach for an online handwritten mathematical expression recognition system
TL;DR: This paper presents an online handwritten mathematics expression recognition system that handles mathematical expression recognition as a simultaneous optimization of expression segmentation, symbol recognition, and 2D structure recognition under the restriction of a mathematical expression grammar.
Journal ArticleDOI
An integrated grammar-based approach for mathematical expression recognition
TL;DR: The statistical framework of a model based on two-dimensional grammars and its associated parsing algorithm is defined and a system that implements this approach is developed and results on the large public dataset of the CROHME international competition are reported.
References
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Journal ArticleDOI
Mathematical expression recognition: a survey
Kam Fai Chan,Dit-Yan Yeung +1 more
TL;DR: This survey paper will review most of the existing work with respect to each of the two major stages of the recognition process, and tries to put emphasis on the similarities and differences between systems.
Journal ArticleDOI
Recognizing mathematical expressions using tree transformation
TL;DR: A robust and efficient system for recognizing typeset and handwritten mathematical notation that allows robust handling of unexpected input, increases the scalability of the system, and provides the groundwork for handling dialects of mathematical notation.
Journal ArticleDOI
An efficient syntactic approach to structural analysis of on-line handwritten mathematical expressions
Kam Fai Chan,Dit-Yan Yeung +1 more
TL;DR: Experiments done on some commonly seen mathematical expressions show that the proposed methods can achieve quite satisfactory speedup, making mathematical expression recognition more feasible for real-world applications.
Proceedings ArticleDOI
Understanding mathematical expressions from document images
TL;DR: This paper proposes a system that understands mathematical expressions on binarized printed document images by extracting a set of "primitives" from the image and constructing an initial hierarchy according to conventional mathematical syntax rules.
Proceedings ArticleDOI
On-line handwritten formula recognition using hidden Markov models and context dependent graph grammars
TL;DR: This paper uses a graph grammar approach for the structure recognition, also used in off-line recognition process, resulting in a general tree-structure of the underlying input-expression, which can be translated to any desired syntax.