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Publications

Displaying results 331 to 340 of 661.

  1. Nijat Mehdiyev; Peter Fettke

    Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring

    In: Witold Pedrycz; Shyi-Ming Chen (Hrsg.). Interpretable Artificial Intelligence: A Perspective of Granular Computing. Chapter 1, Pages 1-28, Vol. 937, ISBN 9783030649487, Springer, 2021.

  2. Viktor Eisenstadt; Hardik Arora; Christoph Ziegler; Jessica Bielski; Christoph Langenhan; Klaus-Dieter Althoff; Andreas Dengel

    Exploring optimal ways to represent topological and spatial features of building designs in deep learning methods and applications for architecture

    In: CAADRIA 2021 Proceedings. International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA-2021), March 29 - April 1, Hong Kong/Virtual, Hong Kong, Cumincad, 2021.

  3. Sk Aziz Ali; Kerem Kahraman; Gerd Reis; Didier Stricker

    RPSRNet: End-to-End Trainable Rigid Point Set Registration Network usingBarnes-Hut 2^D-Tree Representation

    In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). International Conference on Computer Vision and Pattern Recognition (CVPR-2021), June 19-25, Virtual, IEEE, 6/2021.

  4. Wei Jiang; Hans Dieter Schotten

    A Simple Cooperative Diversity Method Based on Deep-Learning-Aided Relay Selection

    In: IEEE Transactions on Vehicular Technology, Vol. 70, Pages 1-16, IEEE, 2021.

  5. Abdul Rafey Aftab; Michael von der Beeck; Michael Feld

    You Have a Point There: Object Selection Inside an Automobile Using Gaze, Head Pose and Finger Pointing

    In: ICMI '20: Proceedings of the 2020 International Conference on Multimodal Interaction. ACM International Conference on Multimodal Interaction (ICMI-2020), October 25-29, Utrecht, Netherlands, Pages 595-603, ISBN 978-1-4503-7581-8/20/10, ACM, 9/2020.

  6. Peter Fettke; Robert Risse; Fritz Esterer

    Anwendungspotentiale von Deep Learning im Process Mining in der Steuerabteilung am Beispiel von Henkel

    In: IM+io, Vol. 4, Pages 84-89, AWSI Publishing, 12/2017.

  7. Ho Minh Duy Nguyen; Duy M. Nguyen; Huong Vu; Binh T. Nguyen; Fabrizio Nunnari; Daniel Sonntag

    An Attention Mechanism using Multiple Knowledge Sources for COVID-19 Detection from CT Images

    In: The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21). AAAI Conference on Artificial Intelligence (AAAI), Workshop on Trustworthy AI for Healthcare, February 2-9, Vancouver, BC, Canada, AAAI, 2021.

  8. Peter Hevesi; Ramprasad Chinnaswamy Devaraj; Matthias Tschöpe; Oliver Petter; Janis Nikolaus Elfert; Vitor Fortes Rey; Marco Hirsch; Paul Lukowicz

    Towards Construction Progress Estimation Based on Images Captured on Site

    In: EAI IndustrialIoT 2020 - 4th EAI International Conference on Industrial IoT Technologies and Applications. EAI International Conference on Industrial IoT Technologies and Applications (EAI IndustrialIoT-2020), December 11, Online-Conference, Springer, 2020.

  9. Lauren Michelle Pfeifer; Matias Valdenegro-Toro

    Automatic Detection and Classification of Tick-borne Skin Lesions using Deep Learning

    In: Workshop: LXAI Research @ NeurIPS 2020. LatinX in AI Research Workshop (LXAI-2020), located at NeurIPS2020, December 7, Virtual, Keine, 2020.

  10. Matthias Rosynski; Frank Kirchner; Matias Valdenegro-Toro

    Are Gradient-based Saliency Maps Useful in Deep Reinforcement Learning?

    In: ICBINB@NeurIPS 2020 - Bridging the gap between theory and empiricism in probabilistic machine learning. I Can't Believe It's Not Better! Workshop (ICBINB-2020), located at NeurIPS 2020, December 12, Virtual, arXiv, 2020.

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