% This file was created with JabRef 2.10.
% Encoding: UTF-8


@Misc{Kirsch2014,
  Title                    = {Detexify data},

  Author                   = {Daniel Kirsch},
  Month                    = jul,
  Year                     = {2014},

  Url                      = {https://github.com/kirel/detexify-data}
}

@MastersThesis{Kirsch,
  Title                    = {Detexify: Erkennung handgemalter {L}a{T}e{X}-Symbole},
  Author                   = {Daniel Kirsch},
  School                   = {Westfälische Wilhelms-Universität Münster},
  Year                     = {2010},
  Month                    = {10},
  Type                     = {Diploma thesis},

  Url                      = {http://danielkirs.ch/thesis.pdf}
}

@Article{LeNet-5,
  Title                    = {Gradient-based learning applied to document recognition},
  Author                   = {LeCun, Yann and Bottou, L{\'e}on and Bengio, Yoshua and Haffner, Patrick},
  Journal                  = {Proceedings of the IEEE},
  Year                     = {1998},

  Month                    = nov,
  Number                   = {11},
  Pages                    = {2278-2324},
  Volume                   = {86},

  Doi                      = {10.1109/5.726791},
  ISSN                     = {0018-9219},
  Keywords                 = {backpropagation;convolution;multilayer perceptrons;optical character recognition;2D shape variability;GTN;back-propagation;cheque reading;complex decision surface synthesis;convolutional neural network character recognizers;document recognition;document recognition systems;field extraction;gradient based learning technique;gradient-based learning;graph transformer networks;handwritten character recognition;handwritten digit recognition task;high-dimensional patterns;language modeling;multilayer neural networks;multimodule systems;performance measure minimization;segmentation recognition;Character recognition;Feature extraction;Hidden Markov models;Machine learning;Multi-layer neural network;Neural networks;Optical character recognition software;Optical computing;Pattern recognition;Principal component analysis},
  Url                      = {http://yann.lecun.com/exdb/publis/pdf/lecun-01a.pdf}
}

@MastersThesis{Thoma:2014,
  Title                    = {On-line {Recognition} of {Handwritten} {Mathematical} {Symbols}},
  Author                   = {Martin Thoma},
  School                   = {Karlsruhe Institute of Technology},
  Year                     = {2014},

  Address                  = {Karlsruhe, Germany},
  Month                    = nov,
  Type                     = {Bachelor’s Thesis},

  Keywords                 = {handwriting recognition; on-line; machine learning;
artificial neural networks; mathematics; classification;
supervised learning; MLP; multilayer perceptrons; hwrt;
write-math},
  Url                      = {http://martin-thoma.com/write-math}
}

@Misc{TF-MNIST-2016,
  Title                    = {Deep MNIST for Experts},
  Month                    = dec,
  Year                     = {2016},

  Url                      = {https://www.tensorflow.org/tutorials/mnist/pros/}
}

