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@MISC{Kiwitz:888499,
      author       = {Kiwitz, Kai and Schiffer, Christian and Spitzer, Hannah and
                      Dickscheid, Timo and Amunts, Katrin},
      title        = {{F}ilter {A}ctivations of {C}onvolutional {N}euronal
                      {N}etworks {U}sed in {C}ytoarchitectonic {B}rain {M}apping},
      publisher    = {EBRAINS},
      reportid     = {FZJ-2020-04963},
      year         = {2020},
      abstract     = {We studied the internal structure of two specific
                      Convolutional Neural Networks (CNNs) which were trained to
                      segment the primary (hOc1, V1) and secondary visual cortex
                      (hOc2, V2) in microscopic scans of brain tissue sections
                      with a resolution of 1 micrometer. All tissue sections
                      correspond to those of the BigBrain dataset ([Amunts et al.,
                      2013](https://science.sciencemag.org/content/340/6139/1472)).
                      To analyze the internal feature representations learned by
                      the model, 5184 filter activations from the batch-normalized
                      output of each Rectified Linear Unit (ReLU) of the CNNs were
                      calculated for section number 1021 of the histological
                      stack. We described and analyzed these filter activations to
                      better understand the internal feature representations of
                      the trained networks. This enables a direct comparison with
                      the underlying histology and a direct assessment of
                      cytoarchitectonic features reflected inside the networks.
                      **Additional information:** The corresponding reference
                      delineations were published in: Kiwitz et al. (2019) [DOI:
                      10.25493/3GSV-T4A](https://kg.ebrains.eu/search/instances/Dataset/87c6dea7-bdf7-4049-9975-6a9925df393f)
                      Kiwitz et al. (2019) [DOI:
                      10.25493/8MKD-D77](https://kg.ebrains.eu/search/instances/Dataset/02b56db7-a083-44f3-91dc-72bb67f3fd0a)},
      cin          = {INM-1},
      cid          = {I:(DE-Juel1)INM-1-20090406},
      pnm          = {574 - Theory, modelling and simulation (POF3-574) / HBP
                      SGA2 - Human Brain Project Specific Grant Agreement 2
                      (785907) / HBP SGA3 - Human Brain Project Specific Grant
                      Agreement 3 (945539)},
      pid          = {G:(DE-HGF)POF3-574 / G:(EU-Grant)785907 /
                      G:(EU-Grant)945539},
      typ          = {PUB:(DE-HGF)32},
      doi          = {10.25493/Z6NG-4MU},
      url          = {https://juser.fz-juelich.de/record/888499},
}