Lecture Notes in Computer Science

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  • 2018 | Book Chapter
    ​ ​Diverse Feature Visualizations Reveal Invariances in Early Layers of Deep Neural Networks​
    Cadena, S. A.; Weis, M. A.; Gatys, L. A.; Bethge, M.; Ecker, A. S.  & Weiss, Y.​ (2018)
    In:​Ferrari, V.; Hebert, M.; Sminchisescu, C.​ (Eds.), Computer Vision – ECCV 2018 pp. 225​-240. (Vol. 11216). ​Cham: ​Springer. DOI: https://doi.org/10.1007/978-3-030-01258-8_14 
    ​Details  DOI 
  • 2010 | Book Chapter
    ​ ​Design Science in Research Cooperations with the Industry: Findings from Three Prototyping Projects​
    Weber, S.; Beck, R.& Gregory, R. W. ​ (2010)
    In:​Winter, R.; Zhao, J. L.; Aier, S.​ (Eds.), Global Perspectives on Design Science Research pp. 534​-537. (Vol. 6105). ​Berlin, Heidelberg: ​Springer. DOI: https://doi.org/10.1007/978-3-642-13335-0_39 
    ​Details  DOI 
  • 2009 | Conference Paper
    ​ ​Introducing Sim-Based Security Tokens as Enabling Technology for Mobile Real-Time Services​
    Roßnagel, H. & Muntermann, J. ​ (2009)
    In:Jøsang, A.; Maseng, T.; Knapskog, S. J.​ (Eds.), ​Identity and Privacy in the Internet Age pp. 163​-178. (Vol. 5838). ​Nordic Conference on Secure IT Systems (NordSec)​, Oslo.
    Berlin, Heidelberg​: Springer. DOI: https://doi.org/10.1007/978-3-642-04766-4_12 
    ​Details  DOI 
  • 2001 | Conference Paper
    ​ ​Bad Design and Good Performance: Strategies of the Visual System for Enhanced Scene Analysis​
    Woergoetter, F. ​ (2001)
    In:Dorffner, Georg; Bischof, Horst; Hornik, Kurt​ (Eds.), ​Artificial Neural Networks — ICANN 2001 pp. 13​-15. ​International Conference on Artificial Neural Networks (ICANN-2001)​, Wien.
    Berlin, Heidelberg​: Springer. DOI: https://doi.org/10.1007/3-540-44668-0_3 
    ​Details  DOI 
  • 2001 | Conference Paper
    ​ ​Temporal Hebbian Learning in Rate-Coded Neural Networks: A Theoretical Approach towards Classical Conditioning​
    Porr, B. & Woergoetter, F. ​ (2001)
    In:Dorffner, Georg; Bischof, Horst; Hornik, Kurt​ (Eds.), ​Artificial Neural Networks — ICANN 2001 pp. 1115​-1120. ​ICANN: International Conference on Artificial Neural Networks​, Vienna.
    Berlin, Heidelberg​: Springer. DOI: https://doi.org/10.1007/3-540-44668-0_155 
    ​Details  DOI 

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