Biblio

Export 177 results:
Author Title Type [ Year(Asc)]
2021
Sick, B., T. Hothorn, and O. Dürr, "Deep transformation models: Tackling complex regression problems with neural network based transformation models", Accepted for Proceedings of the 25th International Conference on Pattern Recognition (ICPR), Milan/Online, 2021, 2021.
2020
Griesser, D., D. Dold, G. Umlauf, and M.O. Franz, "CNN-Based Monocular 3D Ship Detection Using Inverse Perspective", Global Oceans, 2020.
Hake, F., M. Hermann, H. Alkhatib, C. Hesse, K. Holste, G. Umlauf, G. Kermarrec, and I. Neumann, "Damage Detection for Port Infrastructure by Means of Machine-Learning-Algorithms", FIG Working Week 2020, 04/2020.
Pearse, G. D., A. Y. S. Tan, M. S. Watt, M. O. Franz, and J. P. Dash, "Detecting and mapping tree seedlings in UAV imagery using convolutional neural networks and field-verified data", ISPRS Journal of Photogrammetry and Remote Sensing, vol. 168, pp. 156 - 169, 2020.
Herzog, L., E. Murina, O. Dürr, S. Wegener, and B. Sick, "Integrating uncertainty in deep neural networks for MRI based stroke analysis", Medical Image Analysis, vol. 65, pp. 101790, 2020.
Dürr, O., B. Sick, and E. Murina, Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability, : Manning Publications, 2020.
Brach, K., B. Sick, and O. Dürr, "Single Shot MC Dropout Approximation", ICML Workshop on Uncertainty and Robustness in Deep Learning, 2020.
2019
Stadelmann, T., V. Tolkachev, B. Sick, and O. Dürr, "Beyond ImageNet: Deep Learning in Industrial Practice", Applied Data Science: Springer, pp. 205-232, 2019.
Rohrbach, J., T. Rainhard, B. Sick, and O. Dürr, Bone erosion scoring for rheumatoid arthritis with deep convolutional neural networks, , 2019.
Schall, M., M-P. Schambach, and M. O. Franz, "Dissecting Multi-Line Handwriting for Multi-Dimensional Connectionist Classification", 15th IAPR International Conference on Document Analysis and Recognition: IEEE, 2019.
PDF icon Dissecting Multi-Line Handwriting for Multi-Dimensional Connectionist Classification.pdf (553.24 KB)
Schambach, M-P., S. von der Nüll, and M. Schall, "Fast and Reliable Acquisition of Truth Data for Document Analysis using Cyclic Suggest Algorithms", ICDAR-OST: The 2nd International Workshop on Open Services and Tools for Document Analysis: IEEE, 2019.
PDF icon Fast and Reliable Acquisition of Truth Data for Document Analysis using Cyclic Suggest Algorithms.pdf (776.45 KB)
2018
Casanova, R., E. Murina, M. Haberecker, H. Honcharova-Biletska, B. Vrugt, O. Dürr, B. Sick, and A. Soltermann, "Automatic classification of non-small cell lung cancer histologic sub-types by deep learning", VIRCHOWS ARCHIV: Springer, pp. 108-108, 09/18, 2018.
Stadelmann, T., S. Glinski-Haefeli, P. Gerber, and O. Dürr, "Capturing Suprasegmental Features of a Voice with RNNs for Improved Speaker Clustering", IAPR Workshop on Artificial Neural Networks in Pattern Recognition: Springer, pp. 333–345, 2018.
PDF icon ANNPR_2018b.pdf (692.47 KB)
Zirkler, R., T. Eckhard, and B. Jödicke, "A concept for a multi-spectral snap-shot camera based on single-chip RGB sensor", Forum Bildverarbeitung, pp. Poster, 2018.
Laube, P., M. O. Franz, and G. Umlauf, "Deep Learning Parametrization for B-Spline Curve Approximation", 2018 International Conference on 3D Vision (3DV): IEEE, pp. 691–699, 2018.
PDF icon 0109.pdf (675.91 KB)
Siegismund, D., V. Tolkachev, S. Heyse, B. Sick, O. Dürr, and S. Steigele, "Developing deep learning applications for life science and pharma industry", Drug research, vol. 68, pp. 305–310, 2018.
Laube, P., G. Michael, M. O. Franz, and G. Umlauf, "Image Inpainting for High-Resolution Textures using CNN Texture Synthesis", Computer Graphics & Visual Computing (CGVC), Swansea UK, Eurographics Association, 2018.
PDF icon gcvc18.pdf (5.73 MB)
Dürr, O., E. Murina, D. Siegismund, V. Tolkachev, S. Steigele, and B. Sick, "Know When You Don't Know: A Robust Deep Learning Approach in the Presence of Unknown Phenotypes", Assay and drug development technologies, vol. 16, no. 6: Mary Ann Liebert, Inc. 140 Huguenot Street, 3rd Floor New Rochelle, NY 10801 USA, pp. 343–349, 2018.
PDF icon adt.2018.859.pdf (711.06 KB)
Meier, B. Bruno, I. Elezi, M. Amirian, O. Dürr, and T. Stadelmann, "Learning Neural Models for End-to-End Clustering", IAPR Workshop on Artificial Neural Networks in Pattern Recognition: Springer, pp. 126–138, 2018.
PDF icon ANNPR_2018a.pdf (3.43 MB)
Laube, P., M. O. Franz, and G. Umlauf, "Learnt knot placement in B-spline curve approximation using support vector machines", Computer Aided Geometric Design, vol. 62, pp. 104–116, 2018.
PDF icon GMP18.pdf (865.85 KB)
Schall, M., H. P. Buehrig, M-P. Schambach, and M. O. Franz, "LSTM Networks for Edit Distance Calculation with Exchangeable Dictionaries", 13th IAPR International Workshop on Document Analysis Systems: IEEE, 2018.
PDF icon 2018-04 LSTM Networks for Edit Distance Calculation with Exchangeable Dictionaries.pdf (145.78 KB)
Schall, M., M-P. Schambach, and M. O. Franz, "Multi-Dimensional Connectionist Classification: Reading Text in One Step", 13th IAPR International Workshop on Document Analysis Systems: IEEE, 2018.
PDF icon 2018-04 Multi-Dimensional Connectionist Classification Reading Text in One Step.pdf (485.57 KB)
Grunwald, M., M. Hermann, F. Freiberg, and M. O. Franz, "Optical Surface Detection: A novelty detection approach based on CNN-encoded features", SPIE Optics and Photonics, pp. 10752 - 10752 - 13, 10/2018.
Schall, M., D. Sacha, M. Stein, M. O. Franz, and D. A. Keim, "Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition", Visualization in Data Science (VDS at IEEE VIS) 2018, Berlin/Germany, IEEE, 2018.
PDF icon Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition.pdf (1.03 MB)
2017
Laube, P., M. O. Franz, and G. Umlauf, "Evaluation of features for SVM-based classification of geometric primitives in point clouds", Machine Vision Applications (MVA), 2017 Fifteenth IAPR International Conference on: IEEE, pp. 59–62, 2017.
PDF icon paper.pdf (1.5 MB)

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