Skip to main content Skip to main navigation

Publications

Displaying results 501 to 510 of 572.
  1. Christoph Alt; Marc Hübner; Leonhard Hennig

    Improving Relation Extraction by Pre-trained Language Representations

    In: Proceedings of AKBC 2019. Automated Knowledge Base Construction (AKBC-2019), May 20-22, Amherst, Massachusetts, USA, OpenReview, 2019.

  2. Christoph Zetzsche; Ruth Rosenholtz; Noshaba Cheema; Konrad Gadzicki; Lex Fridman; Kerstin Schill

    Neural Computation of Statistical Image Properties in Peripheral Vision

    In: Vision Science Society (Hrsg.). MODVIS. Computational and Mathematical Models in Vision (MODVIS-2017), located at Vision Sciences Society Annual Meeting, May 17-19, St. Pete Beach, FL, USA, Purdue University, 5/2017.

  3. Jameel Malik; Ahmed Elhayek; Sheraz Ahmed; Faisal Shafait; Muhammad Imran Malik; Didier Stricker

    3DAirSig: A Framework for Enabling In-Air Signatures Using a Multi-Modal Depth Sensor

    In: Sensors - Open Access Journal (Sensors), Vol. 18, No. 11, Page 3872, MDPI AG, Basel, Switzerland, 11/2018.

  4. Gabriel Mittag; Sebastian Möller

    Non-intrusive Estimation of Packet Loss Rates in Speech Communication Systems Using Convolutional Neural Networks

    In: 2018 IEEE International Symposium on Multimedia (ISM). IEEE International Symposium on Multimedia (ISM-2018), December 10-12, Taichung, Taiwan, Province of China, Pages 105-109, ISBN 978-1-5386-6857-3, IEEE, 2018.

  5. Combining Software-Based Eye Tracking and a Wide-Angle Lens for Sneaking Detection

    In: Proc. UbiComp2018 Adjunct (Hrsg.). The 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing. International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp-2018), October 8-12, Singapore, Singapore, Pages 54-57, ISBN 978-1-4503-5966-5, ACM, 2018.

  6. Mohsin Munir; Muhammad Shoaib Ahmed Siddiqui; Andreas Dengel; Sheraz Ahmed

    DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series

    In: IEEE Access, Vol. 7, Pages 1991-2005, IEEE, 12/2018.

  7. Patrick Lübbecke; Nijat Mehdiyev; Peter Fettke

    Substitution of hazardous chemical substances using Deep Learning and t-SNE

    In: Proceedings der Internationalen Tagung Wirtschaftsinformatik. Internationale Tagung Wirtschaftsinformatik (WI-2019), Human Practice. Digital Ecologies. Our Future. February 24-27, Siegen, Germany, AIS, 2019.

  8. Preparation for Future Learning: Augmented-Reality Enhanced Interactive Physics Labs

    In: Proceedings of the International Conference on Ubiquitous Computing. International Conference on Ubiquitous Computing (Ubicomp-2018), October 8-12, Singapore, Singapore, Pages 331-334, ISBN 978-1-4503-5966-5/18/10, ACM, 2018.

  9. Nijat Mehdiyev; Joerg Evermann; Peter Fettke

    A Novel Business Process Prediction Model Using a Deep Learning Method

    In: Springer Fachmedien Wiesbaden (Hrsg.). Business & Information Systems Engineering (BISE), Vol. 5/2018, Pages 1-15, Springer Fachmedien, Wiesbaden, 7/2018.

  10. Kareem Amin; Stelios Kapetanakis; Klaus-Dieter Althoff; Andreas Dengel; Miltos Petridis

    Answering with Cases: A CBR Approach to Deep Learning

    In: Michael T. Cox; Peter Funk; Shahina Begum (Hrsg.). Case-Based Reasoning Research and Development. International Conference on Case-Based Reasoning (ICCBR-2018), July 9-12, Stockholm, Sweden, Springer, 12/2018.