A Bayesian model for recognizing handwritten mathematical expressions

18 Sep 2014Scott MacLeanGeorge Labahn

Recognizing handwritten mathematics is a challenging classification problem, requiring simultaneous identification of all the symbols comprising an input as well as the complex two-dimensional relationships between symbols and subexpressions. Because of the ambiguity present in handwritten input, it is often unrealistic to hope for consistently perfect recognition accuracy... (read more)

PDF Abstract

Code


No code implementations yet. Submit your code now

Tasks


Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet