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Publications

 

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Displaying results 31 to 40 of 513.
  1. Ekaterina Loginova; Stalin Varanasi; Günter Neumann

    Towards End-to-End Multilingual Question Answering

    In: Information Systems Frontiers (ISF), Vol. 22, Pages 1-14, Springer, 3/2020.

  2. Early Verification of ISA Extension Specifications Using Deep Reinforcement Learning

    In: 30th ACM Great Lakes Symposium on VLSI (GLSVLSI). ACM Great Lakes Symposium on VLSI (GLSVLSI-2020), Beijing, China, 2020.

  3. AutoPOSE: Large-Scale Automotive Driver Head Pose and Gaze Dataset with Deep Head Pose Baseline

    In: International Conference on Computer Vision Theory and Applications (VISAPP). International Conference on Computer Vision Theory and Applications …

  4. 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 …

  5. 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 …

  6. 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.

  7. Simple and effective deep hand shape and pose regression from a single depth image

    In: Computers & Graphics (CAG), Vol. 85, Pages 85-91, ELSEVIER, 10/2019.

  8. Tim Dahmen; Pavel Potocek; Patrick Trampert; Maurice Peemen; Remco Schoenmakers

    Sparse Scanning Electron Microscopy and Deep Learning for Imaging and Segmentation of Neuron Structures

    In: Microscopy & Microanalysis 25. Microscopy & Microanalysis (M&M-2019), August 4-8, Portland, Oregon, USA, Cambridge University Press, 8/2019.

  9. Tim Dahmen; Patrick Trampert; Faysal Boughorbel; Janis Sprenger; Matthias Klusch; Klaus Fischer; Christian Kübel; Philipp Slusallek

    Digital reality: a model-based approach to supervised learning from synthetic data

    In: AI Perspectives, Vol. 1, Pages 1-12, Springer, 2019.

  10. Patrick Trampert; Sabine Schlabach; Tim Dahmen; Philipp Slusallek

    Deep Learning for Sparse Scanning Electron Microscopy

    In: Microscopy and Microanalysis 25. Microscopy & Microanalysis (M&M-2019), August 4-8, Portland, Oregon, USA, Cambridge University Press, 2019.