Biblio

Export 238 results:
Author Title Type [ Year(Asc)]
2020
Dürr, O., Sick B., & Murina E. (2020).  Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability.
Dürr, O., Sick B., & Murina E. (2020).  Probabilistic deep learning: With python, keras and tensorflow probability.
Brach, K., Sick B., & Dürr O. (2020).  Single Shot MC Dropout Approximation. ICML Workshop on Uncertainty and Robustness in Deep Learning.
2019
Stadelmann, T., Tolkachev V., Sick B., & Dürr O. (2019).  Beyond ImageNet: Deep Learning in Industrial Practice. Applied Data Science. 205-232.
Rohrbach, J., Rainhard T., Sick B., & Dürr O. (2019).  Bone erosion scoring for rheumatoid arthritis with deep convolutional neural networks.
Schall, M., Schambach M-P., & Franz M. O. (2019).  Dissecting Multi-Line Handwriting for Multi-Dimensional Connectionist Classification. 15th IAPR International Conference on Document Analysis and Recognition. PDF icon Dissecting Multi-Line Handwriting for Multi-Dimensional Connectionist Classification.pdf (553.24 KB)
Schambach, M-P., von der Nüll S., & Schall M. (2019).  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. PDF icon Fast and Reliable Acquisition of Truth Data for Document Analysis using Cyclic Suggest Algorithms.pdf (776.45 KB)
2018
Casanova, R., Murina E., Haberecker M., Honcharova-Biletska H., Vrugt B., Dürr O., et al. (2018).  Automatic classification of non-small cell lung cancer histologic sub-types by deep learning. VIRCHOWS ARCHIV. 108-108.
Stadelmann, T., Glinski-Haefeli S., Gerber P., & Dürr O. (2018).  Capturing Suprasegmental Features of a Voice with RNNs for Improved Speaker Clustering. IAPR Workshop on Artificial Neural Networks in Pattern Recognition. 333–345.PDF icon ANNPR_2018b.pdf (692.47 KB)
Zirkler, R., Eckhard T., & Jödicke B. (2018).  A concept for a multi-spectral snap-shot camera based on single-chip RGB sensor. Forum Bildverarbeitung. Poster.
Laube, P., Franz M. O., & Umlauf G. (2018).  Deep Learning Parametrization for B-Spline Curve Approximation. 2018 International Conference on 3D Vision (3DV). 691–699.PDF icon 0109.pdf (675.91 KB)
Siegismund, D., Tolkachev V., Heyse S., Sick B., Dürr O., & Steigele S. (2018).  Developing deep learning applications for life science and pharma industry. Drug research. 68, 305–310.
Bohnet, D., & Vartziotis D. (2018).  Fractal Curves from Prime Trigonometric Series. Fractal Fract.. 2(2), 
Bohnet, D., Himpel B., & Vartziotis D. (2018).  GETOpt mesh smoothing: Putting GETMe in the framework of global optimization-based schemes. Finite Elem. Anal. Des.. 147,
Laube, P., Michael G., Franz M. O., & Umlauf G. (2018).  Image Inpainting for High-Resolution Textures using CNN Texture Synthesis. Computer Graphics & Visual Computing (CGVC). PDF icon gcvc18.pdf (5.73 MB)
Dürr, O., Murina E., Siegismund D., Tolkachev V., Steigele S., & Sick B. (2018).  Know When You Don't Know: A Robust Deep Learning Approach in the Presence of Unknown Phenotypes. Assay and drug development technologies. 16, 343–349.PDF icon adt.2018.859.pdf (711.06 KB)
Meier, B. Bruno, Elezi I., Amirian M., Dürr O., & Stadelmann T. (2018).  Learning Neural Models for End-to-End Clustering. IAPR Workshop on Artificial Neural Networks in Pattern Recognition. 126–138.PDF icon ANNPR_2018a.pdf (3.43 MB)
Meier, B. Bruno, Stadelmann T., & Dürr O. (2018).  Learning to Cluster. PDF icon learning_to_cluster.pdf (1.82 MB)
Laube, P., Franz M. O., & Umlauf G. (2018).  Learnt knot placement in B-spline curve approximation using support vector machines. Computer Aided Geometric Design. 62, 104–116.PDF icon GMP18.pdf (865.85 KB)
Schall, M., Buehrig H. P., Schambach M-P., & Franz M. O. (2018).  LSTM Networks for Edit Distance Calculation with Exchangeable Dictionaries. 13th IAPR International Workshop on Document Analysis Systems. PDF icon 2018-04 LSTM Networks for Edit Distance Calculation with Exchangeable Dictionaries.pdf (145.78 KB)
Schall, M., Schambach M-P., & Franz M. O. (2018).  Multi-Dimensional Connectionist Classification: Reading Text in One Step. 13th IAPR International Workshop on Document Analysis Systems. PDF icon 2018-04 Multi-Dimensional Connectionist Classification Reading Text in One Step.pdf (485.57 KB)
Grunwald, M., Hermann M., Freiberg F., & Franz M. O. (2018).  Optical Surface Detection: A novelty detection approach based on CNN-encoded features. SPIE Optics and Photonics. 10752 - 10752 - 13.PDF icon Spie2018.pdf (730 KB)
Schall, M., Sacha D., Stein M., Franz M. O., & Keim D. A. (2018).  Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition. Visualization in Data Science (VDS at IEEE VIS) 2018. PDF icon Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition.pdf (1.03 MB)
2017
Hermann, M., Madrid N., & Seepold R. (2017).  Detection of variations in holter ECG recordings based on dynamic cluster analysis. International Conference on Intelligent Decision Technologies.
Laube, P., Franz M. O., & Umlauf G. (2017).  Evaluation of features for SVM-based classification of geometric primitives in point clouds. Machine Vision Applications (MVA), 2017 Fifteenth IAPR International Conference on. 59–62.PDF icon paper.pdf (1.5 MB)

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