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@INPROCEEDINGS{Esmail:868236,
      author       = {Esmail, W. and Stockmanns, T. and Ritman, J.},
      title        = {{M}achine {L}earning for {T}rack {F}inding at {PANDA}},
      reportid     = {FZJ-2019-06797, PROC-CTD19-091},
      year         = {2019},
      abstract     = {We apply deep learning methods as a track finding algorithm
                      to the PANDA Forward Tracking Stations (FTS). The problem is
                      divided into three steps: The first step relies on an
                      Artificial Neural Network (ANN) that is trained as a binary
                      classifier to build track segments in three different parts
                      of the FTS, namely FT1,FT2, FT3,FT4, and FT5,FT6. The ANN
                      accepts hit pairs as an input and outputs a probability that
                      they are on the same track or not. The second step builds 3D
                      track segments from the 2D ones and is based on the geometry
                      of the detector. The last step is to match the track
                      segments from the different parts of the FTS to form a full
                      track candidate, and is based on a Recurrent Neural Network
                      (RNN). The RNN is used also as a binary classifier that
                      outputs the probability that the combined track segments are
                      a true track or not. The performance of the algorithm is
                      judged based on the purity, efficiency and the ghost ratio
                      of the reconstructed tracks. The purity specifies which
                      fraction of hits in one track come from the correct
                      particle. The correct particle is the particle, which
                      produces the majority of hits in the track. The efficiency
                      is defined as the ratio of the number of correctly
                      reconstructed tracks to all generated tracks.},
      month         = {Apr},
      date          = {2019-04-02},
      organization  = {Connecting the Dots and Workshop on
                       Intelligent Trackers (CTD/WIT2019),
                       Valencia (Spain), 2 Apr 2019 - 5 Apr
                       2019},
      subtyp        = {Other},
      cin          = {IKP-1},
      cid          = {I:(DE-Juel1)IKP-1-20111104},
      pnm          = {6G12 - FAIR (POF3-624)},
      pid          = {G:(DE-HGF)POF3-6G12},
      typ          = {PUB:(DE-HGF)29 / PUB:(DE-HGF)6},
      eprint       = {1910.07191},
      howpublished = {arXiv:1910.07191},
      archivePrefix = {arXiv},
      SLACcitation = {$\%\%CITATION$ = $arXiv:1910.07191;\%\%$},
      url          = {https://juser.fz-juelich.de/record/868236},
}