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Assistant Professorship for Intelligent Information Systems
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  1. Friedrich-Alexander-Universität
  2. School of Business, Economics and Society

Assistant Professorship for Intelligent Information Systems

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  • About us
    • Our Team
      • Prof. Dr. Patrick Zschech
      • Nico Hambauer
      • Nazar El Saifi
      • Christopher Wissuchek
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        • Juliane Ort
        • Julian Rosenberger
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  • Research
    • Interpretable Machine Learning
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    • Deep Vision Systems
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  • Teaching
    • Bachelor
      • Business Analytics: Technologien, Methoden und Konzepte
    • Master
      • Development of Deep Vision Systems
      • Natural Language Processing for Business Analytics
      • Business Analytics: Case Studies (Winter Term)
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      • Business Analytics: Research Seminar (Summer Term)
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  1. Home
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  3. Deep Vision Systems

Deep Vision Systems

In page navigation: Research
  • Interpretable Machine Learning
  • Industrial Data Science
  • Deep Vision Systems
  • Process Analytics
  • AI Adoption and Use
  • Data Science Qualification
  • Other Research
  • Publications
    • Journal Articles
    • Conference Articles
    • Book Chapters
    • Thesis
    • Others
  • Talks

Deep Vision Systems

The research field is concerned with the design, analysis, and use of intelligent information systems based on deep learning methods in the field of computer vision.

Publications

  • Heinrich K., Zschech P., Möller B., Breithaupt L., Maresch J.:
    Objekterkennung im Weinanbau – Eine Fallstudie zur Unterstützung von Winzertätigkeiten mithilfe von Deep Learning
    In: HMD : Praxis der Wirtschaftsinformatik 56 (2019), p. 964-985
    ISSN: 1436-3011
    DOI: 10.1365/s40702-019-00514-9
    URL: https://link.springer.com/article/10.1365/s40702-019-00514-9
  • Zschech P., Sager C., Siebers P., Pertermann M.:
    Mit Computer Vision zur automatisierten Qualitätssicherung in der industriellen Fertigung: Eine Fallstudie zur Klassifizierung von Fehlern in Solarzellen mittels Elektrolumineszenz-Bildern
    In: HMD : Praxis der Wirtschaftsinformatik (2021), p. 321–342
    ISSN: 1436-3011
    DOI: 10.1365/s40702-020-00641-8
    URL: https://link.springer.com/article/10.1365/s40702-020-00641-8
  • Heinrich K., Roth A., Zschech P.:
    Everything Counts: A Taxonomy of Deep Learning Approaches for Object Counting
    27th European Conference on Information Systems (ECIS) (Stockholm & Uppsala, 8. June 2019 - 14. June 2019)
    In: Proceedings of the 27th European Conference on Information Systems 2019
    URL: https://aisel.aisnet.org/ecis2019_rp/63/
  • Friederich J., Zschech P.:
    Review and Systematization of Solutions for 3D Object Detection
    15th International Conference on Wirtschaftsinformatik (WI) (Potsdam, 8. March 2020 - 11. March 2020)
    In: Gronau N, Heine M, Krasnova H, Pousttchi K (ed.): Proceedings of the 15th International Conference on Wirtschaftsinformatik, Berlin: 2020
    DOI: 10.30844/wi_2020_r2-friedrich
    URL: https://library.gito.de/oa_wi2020-r2.html
  • Heinrich K., Graf J., Chen J., Laurisch J., Zschech P.:
    Fool Me Once, Shame On You, Fool Me Twice, Shame On Me: A Taxonomy of Attack and Defense Patterns for AI Security
    28th European Conference on Information Systems (ECIS) (Virtual Conference, 15. June 2020 - 17. June 2020)
    In: Association for Information Systems (ed.): Proceedings of the 28th European Conference on Information Systems 2020
    URL: https://aisel.aisnet.org/ecis2020_rp/166/
  • Heinrich K., Möller B., Janiesch C., Zschech P.:
    Is Bigger Always Better? Lessons Learnt from the Evolution of Deep Learning Architectures for Image Classification
    Pre-ICIS SIGDSA Symposium (Munich, 14. December 2019 - 15. December 2019)
    In: Proceedings of the Pre-ICIS SIGDSA Symposium 2019
    URL: https://aisel.aisnet.org/sigdsa2019/20/
  • Sager C., Janiesch C., Zschech P.:
    A Survey of Image Labelling for Computer Vision Applications
    In: Journal of Business Analytics 4 (2021), p. 91-110
    ISSN: 2573-234X
    DOI: 10.1080/2573234X.2021.1908861
  • Janiesch C., Zschech P., Heinrich K.:
    Machine Learning and Deep Learning
    In: Electronic Markets 31 (2021), p. 685–695
    ISSN: 1019-6781
    DOI: 10.1007/s12525-021-00475-2
    URL: https://link.springer.com/article/10.1007/s12525-021-00475-2
  • Zschech P., Heinrich K., Möller B., Breithaupt L., Maresch J., Roth A.:
    Deep Learning in der Landwirtschaft – Analyse eines Weinbergs
    In: D'Onofrio S., Meier A. (ed.): Big Data Analytics, 2021, p. 169-194
    ISBN: 9783658322359

    DOI: 10.1007/978-3-658-32236-6_8
    URL: https://link.springer.com/chapter/10.1007/978-3-658-32236-6_8
  • Zschech P., Walk J., Heinrich K., Vössing M., Kühl N.:
    A Picture is Worth a Collaboration: Accumulating Design Knowledge for Computer-Vision-based Hybrid Intelligence Systems
    29th European Conference on Information Systems (ECIS) (Virtual Conference, 14. June 2021 - 16. June 2021)
    In: Proceedings of the 29th European Conference on Information Systems (ECIS) 2021
    URL: https://aisel.aisnet.org/ecis2021_rp/127/
  • Sager C., Zschech P., Kühl N.:
    labelCloud: A Lightweight Domain-Independent Labeling Tool for 3D Object Detection in Point Clouds
    International CAD Conference (Barcelona, 5. July 2021 - 7. July 2021)
    In: Proceedings of CAD’21 2021
    DOI: 10.14733/cadconfP.2021.319-323
  • Harl M., Herchenbach M., Kruschel S., Hambauer N., Zschech P., Kraus M.:
    A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
    In: Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI) 2022
    Open Access: https://aisel.aisnet.org/wi2022/student_track/student_track/33/
    URL: https://aisel.aisnet.org/wi2022/student_track/student_track/33/
  • Sager C., Zschech P., Kühl N.:
    labelCloud: A Lightweight Labeling Tool for Domain-Agnostic 3D Object Detection in Point Clouds
    In: Computer-Aided Design and Applications 19 (2022), p. 1191-1206
    ISSN: 1686-4360
    DOI: 10.14733/cadaps.2022.1191-1206
    URL: http://cad-journal.net/files/vol_19/CAD_19(6)_2022_1191-1206.pdf
  • Heinrich K., Zschech P., Skouti T., Griebenow J., Riechert S.:
    Demystifying the Black Box: A Classification Scheme for Interpretation and Visualization of Deep Intelligent Systems
    25th Americas Conference on Information Systems (AMCIS) (Cancún, 15. August 2019 - 17. August 2019)
    In: Proceedings of the 25th Americas Conference on Information Systems 2019
    URL: https://aisel.aisnet.org/amcis2019/ai_semantic_for_intelligent_info_systems/ai_semantic_for_intelligent_info_systems/8/
FAU Erlangen-Nürnberg
Assistant Professorship for Intelligent Information Systems

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90403 Nürnberg
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