@InProceedings{10.20532/ccvw.2019.0008,
  author =       {Gali{\' c}, Vlado and Hrka{\' c}, Tomislav},
  title =        {System for Recognition and Evaluation of Handwritten
                  Arithmetic Expressions},
  year =         2018,
  address =      {Zagreb},
  month =        {October},
  organization = {Center of Excellence for Computer Vision},
  publisher =    {University of Zagreb},
  abstract =     {Recognition of mathematical expressions today is a
                  very interesting area of application of deep
                  learning. The problem is quite complex and requires
                  a complex system to solve it. The problem becomes
                  even more complex if arithmetic expressions are
                  handwritten. The use of convolutional neural
                  networks yields satisfactory results but leaves some
                  room for improvement. In this paper, a simplified
                  variant of the above problem is solved by using an
                  approach that consists of extraction and
                  classification of individual symbols using
                  convolutional neural networks followed by syntactic
                  parsing of the expression taking into account the
                  symbol positions.},
  doi =          {10.20532/ccvw.2019.0008},
  url =          {https://doi.org/10.20532/ccvw.2019.0008}
}