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Publications

Displaying results 371 to 380 of 682.
  1. Johannes Lahann; Peter Pfeiffer; Peter Fettke

    LSTM-based Anomaly Detection of Process Instances: Benchmark and Tweaks

    In: Proceedings of the 4th International Conference on Process Mining (Workshops). International Conference on Process Mining (ICPM-2022), Process Mining Workshops, October 23-28, Bolzano, Italy, Lecture Notes in Business Information Processing, Springer, 2023.

  2. Ground Interaction Models for Increased Autonomy of Planetary Exploration Systems

    In: 13th EASN International Conference on Innovation in Aviation & Space for opening New Horizons (13th EASN 2023). EASN International Conference on Innovation in Aviation and Space for opening New Horizons, September 5-8, Salerno, Italy, Journal of Physics: Conference Series (JPCS), Vol. 2716, IOP Publishing Ltd, 3/2024.

  3. Daniel Sonntag; Fabrizio Nunnari; Hans-Jürgen Profitlich

    The Skincare project, an interactive deep learning system for differential diagnosis of malignant skin lesions.

    Technical Report, BMBF, H2020, DFKI Research Reports (RR), Vol. 1, 5/2020.

  4. Adriano Lucieri; Huzaifa Sabir; Muhammad Shoaib Ahmed Siddiqui; Syed Tahseen Raza Rizvi; Brian Kenji Iwana; Seiichi Uchida; Andreas Dengel; Sheraz Ahmed

    Benchmarking Deep Learning Models for Classification of Book Covers

    In: Springer Singapore (Hrsg.). SN Computer Science, Vol. 1, No. Issue 3, Pages 1-16, Springer, Singapore, 5/2020.

  5. Tewodros Amberbir Habtegebrial; Gerd Reis; Didier Stricker

    Deep Convolutional Networks For Snapshot Hyperspectral Demosaicking

    In: 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS-2019), located at 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), September 24-26, Amsterdam, Netherlands, ISBN Electronic ISBN: 978-1-7281-5294-3, IEEE, 9/2019.

  6. A Comparative Analysis of Traditional and Deep Learning-based Anomaly Detection Methods for Streaming Data

    In: 18th IEEE International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications (ICMLA-2019), December 16-19, Boca Raton, Florida, USA, Pages 561-566, ISBN 978-1-7281-4550-1, IEEE, 12/2019.

  7. Rodrigo Suarez‑Ibarrola; Simon Hein; Gerd Reis; Christian Gratzke; Arkadiusz Miernik

    Current and future applications of machine and deep learning in urology: a review of the literature on urolithiasis, renal cell carcinoma, and bladder and prostate cancer

    In: World Journal of Urology (WJUR), Vol. 2018, Pages 1-19, Springer-Verlag GmbH Germany, part of Springer Nature 2019, 2019.