R-GRU: Regularized gated recurrent unit for handwritten mathematical expression recognition
Abstract: Handwritten mathematical expression recognition(HMER) plays a wide variety of roles in different domains like online teaching, scientific research, etc. Due to its two-dimensional non-linear structure, it is a challenging problem. In this work, we proposed a novel architecture using regularization(dropout), attention & gated recurrent unit(R-GRU). R-GRU is used as the central decoding unit that takes the intermediate representation produced by the encoder as an input and generates corresponding LaTeX sequences. Simulation on CROHME 2014 and 2016 datasets achieve results comparable to the latest state-of-the-art.
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