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Unravelling Representations in Scene-selective Brain Regions Using Scene Parsing Deep Neural Networks

Kshitij Dwivedi, Radoslaw Martin Cichy, View ORCID ProfileGemma Roig
doi: https://doi.org/10.1101/2020.03.10.985309
Kshitij Dwivedi
1Department of Education and Psychology, Free Universität Berlin, Germany
2Department of Computer Science, Goethe University, Frankfurt am Main, Germany
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  • For correspondence: roig@cs.uni-frankfurt.edu rmcichy@zedat.fu-berlin.de kshitijdwivedi93@gmail.com
Radoslaw Martin Cichy
1Department of Education and Psychology, Free Universität Berlin, Germany
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  • For correspondence: roig@cs.uni-frankfurt.edu rmcichy@zedat.fu-berlin.de kshitijdwivedi93@gmail.com
Gemma Roig
2Department of Computer Science, Goethe University, Frankfurt am Main, Germany
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  • ORCID record for Gemma Roig
  • For correspondence: roig@cs.uni-frankfurt.edu rmcichy@zedat.fu-berlin.de kshitijdwivedi93@gmail.com
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Article Information

doi 
https://doi.org/10.1101/2020.03.10.985309
History 
  • March 10, 2020.
Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.

Author Information

  1. Kshitij Dwivedi1,2,*,
  2. Radoslaw Martin Cichy1,†,* and
  3. Gemma Roig2,†,*
  1. 1Department of Education and Psychology, Free Universität Berlin, Germany
  2. 2Department of Computer Science, Goethe University, Frankfurt am Main, Germany
  1. ↵*To whom correspondence should be addressed: E-mail: roig{at}cs.uni-frankfurt.edu; rmcichy{at}zedat.fu-berlin.de; kshitijdwivedi93{at}gmail.com
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Posted March 10, 2020.
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Unravelling Representations in Scene-selective Brain Regions Using Scene Parsing Deep Neural Networks
Kshitij Dwivedi, Radoslaw Martin Cichy, Gemma Roig
bioRxiv 2020.03.10.985309; doi: https://doi.org/10.1101/2020.03.10.985309
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Unravelling Representations in Scene-selective Brain Regions Using Scene Parsing Deep Neural Networks
Kshitij Dwivedi, Radoslaw Martin Cichy, Gemma Roig
bioRxiv 2020.03.10.985309; doi: https://doi.org/10.1101/2020.03.10.985309

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