@InProceedings{10.20532/ccvw.2018.0002,
  author =       {Ko{\v s}{\v c}evi{\' c}, Karlo and Suba{\v s}i{\'
                  c}, Marko},
  title =        {Automatic Visual Reading of Meters Using Deep
                  Learning},
  booktitle =    {Proceedings of the Croatian Compter Vision Workshop,
                  Year 6},
  pages =        {1-6},
  year =         2018,
  editor =       {Lon{\v c}ari{\' c}, Sven and Petkovi{\' c},
                  Tomislav},
  address =      {Zagreb},
  month =        {October},
  organization = {Center of Excellence for Computer Vision},
  publisher =    {University of Zagreb},
  abstract =     {In this paper, we present a novel approach to the
                  problem of reading residential meters using deep
                  learning algorithms. As a starting point we use
                  Faster R-CNN method and, to acquire more precise
                  readings, we modify its functionality.  As there
                  were no databases for this kind of task, one had to
                  be collected and properly annotated. This paper also
                  provides a brief introduction to methods for image
                  augmentation and a technique to augment annotated
                  image dataset. For each part of the presented method
                  as well as the whole method as one unit experiments
                  were conducted to show the overall successfulness.},
  doi =          {10.20532/ccvw.2018.0002},
  url =          {https://doi.org/10.20532/ccvw.2018.0002}
}