Biblio

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A
Seepold, R., Dermati C., Kostka A., Pfeil L., Lange R., Hermann M., et al. (2016).  Analyzing environmental conditions and vital signs to increase healthy living. Mobile Networks for Biometric Data Analysis.
C
Kienzle, W., Wichmann F. A., Schölkopf B., & Franz M. O. (2007).  Center-surround filters emerge from optimizing predictivity in a free-viewing task. {Proc. of the Computational and Systems Neuroscience Meeting 2007 (COSYNE 2007)}.
Kienzle, W., Franz M. O., & Schölkopf B. (2009).  Center-surround patterns emerge as optimal predictors for human saccade targets. J. of Vision. 9, 1–15.PDF icon Kienzle, Franz, Schölkopf_2009_Center-surround patterns emerge as optimal predictors for human saccade targets.pdf (900.5 KB)
Schuldt, T., Döringshoff K., Stühler J., Kovalchuk E., Franz M. O., Gohlke M., et al. (2013).  A compact high-performance frequency reference for space applications. {29th Intl. Symposium on Space Technology and Science (ISTS 2013), Nagoya (Japan)}. PDF icon Schuldt et al._2013_A Compact High-Performance Frequency Reference for Space Applications.pdf (369.85 KB)
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Hake, F., Hermann M., Alkhatib H., Hesse C., Holste K., Umlauf G., et al. (2020).  Damage Detection for Port Infrastructure by Means of Machine-Learning-Algorithms. FIG Working Week 2020. PDF icon Fig2020.pdf (876.57 KB)
Kook, L., Herzog L., Hothorn T., Dürr O., & Sick B. (2020).  Deep and interpretable regression models for ordinal outcomes. arXiv preprint. 2010.08376.
Kook, L., Herzog L., Hothorn T., Dürr O., & Sick B. (2022).  Deep and interpretable regression models for ordinal outcomes. Pattern Recognition. 122, 108263.
Herzog, L., Kook L., Götschi A., Petermann K., Hänsel M., Hamann J., et al. (2023).  Deep transformation models for functional outcome prediction after acute ischemic stroke. Biometrical Journal. 65, 2100379.
Schuldt, T., Schubert C., Krutzik M., Bote L., Gaaloul N., Hartwig J., et al. (2015).  Design of a dual species atom interferometer for space. Experimental Astronomy. 39, 167-206.PDF icon Schuldt et al._2015_Design of a dual species atom interferometer for space.pdf (2.98 MB)
Schuldt, T., Schubert C., Krutzik M., Bote L., Gaaloul N., Hartwig J., et al. (2015).  Design of a dual species atom interferometer for space. Experimental Astronomy. 39, 167-206.PDF icon Schuldt et al._2015_Design of a dual species atom interferometer for space.pdf (2.98 MB)
E
Kienzle, W., Bakır G. H., & Franz M. O. (2004).  Efficient approximations for support vector machines for object detection. (Rasmussen, C. E., Bülthoff H. H., & Giese M. A., Ed.).{Pattern Recognition, Proc. of the 26th DAGM Symposium}. 54–61.PDF icon Kienzle, Bakır, Franz_2004_Efficient approximations for support vector machines for object detection.pdf (165.13 KB)
Hoher, P., Reuter J., Dold D., Griesser D., Govaers F., & Koch W. (2023).  Extended Target Tracking With a Lidar Sensor Using Random Matrices and a Gaussian Processes Regression Model. International Conference on Information Fusion (FUSION). 1-8.
Dahmen, H.-J., Franz M. O., & Krapp H. G. (2001).  Extracting egomotion from optic flow: limits of accuracy and neural matched filters. (Zanker, J. M., & Zeil J., Ed.).{Motion Vision: Computational, Neural and Ecological Constraints}. 143-168.PDF icon Dahmen, Franz, Krapp_2001_Extracting egomotion from optic flow- limits of accuracy and neural matched filters.pdf (223.04 KB)
F
Kienzle, W., Bakır G. H., Franz M. O., & Schölkopf B. (2005).  Face detection – efficient and rank deficient. (Saul, L. K., Weiss Y., & Bottou L., Ed.).{Advances in Neural Information Processing Systems 17}. 673–680.PDF icon Kienzle et al._2005_Face Detection --- Efficient and Rank Deficient.pdf (145.73 KB)
G
Franzini, A., Baty F., Macovei I. I., Dürr O., Droege C., Betticher D., et al. (2015).  Gene expression signatures predictive of bevacizumab/erlotinib therapeutic benefit in advanced non-squamous non-small cell lung cancer patients (SAKK 19/05 trial). Clinical Cancer Research. clincanres––3135.
H
Ilg, W., Bakır G. H., Franz M. O., & Giese M. A. (2003).  Hierarchical spatio-temporal morphable models for representation of complex movements for imitation learning. (Nunes, U., de Almeida A., Bejczy A., Kosuge K., & Machado J., Ed.).{Proc. of the 11th International Conference on Advanced Robotics}. 2, 453–458.PDF icon Ilg et al._2003_Hierarchical spatio-temporal morphable models for representation of complex movements for imitation learning.pdf (716.98 KB)
Kienzle, W., Schölkopf B., Wichmann F. A., & Franz M. O. (2007).  How to find interesting locations in video: a spatiotemporal interest point detector learned from human eye movements. {Lecture Notes in Computer Science: Pattern Recognition (DAGM 2007)}. 405–417.PDF icon Kienzle et al._2007_How to find interesting locations in video a spatiotemporal interest point detector learned from human eye movements.pdf (377.26 KB)
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Franz, M. O., Chahl J. S., & Krapp H. G. (2004).  Insect-inspired estimation of egomotion.. Neural Computation. 16, 2245–60.
Kim, K. I., Franz M. O., & Schölkopf B. (2005).  Iterative kernel principal component analysis for image modeling. IEEE Trans. PAMI. 27, 1351 – 1366.PDF icon Kim, Franz, Schölkopf_2005_Iterative Kernel Principal Component Analysis for Image Modeling.pdf (1.98 MB)
K
Kim, K. I., Franz M. O., & Schölkopf B. (2004).  Kernel Hebbian algorithm for single-frame super-resolution. {Statistical Learning in Computer Vision (SLCV 2004), ECCV 2004 Workshop, Prague}. 135–149.PDF icon Kim, Franz, Schölkopf_2004_Kernel Hebbian algorithm for single-frame super-resolution.pdf (2.22 MB)
L
Kienzle, W., Wichmann F. A., Schölkopf B., & Franz M. O. (2005).  Learning an interest operator from eye movements. {Proc. Workshop on Bioinspired Information Processing 2005}. PDF icon Kienzle et al._2006_Learning an Interest Operator from Human Eye Movements.pdf (1.41 MB)
Kienzle, W., Wichmann F. A., Schölkopf B., & Franz M. O. (2006).  Learning an interest operator from human eye movements. (Schmid, C., Soatto S., & Tomasi C., Ed.).{Beyond Patches Workshop, Intl. Conf. on Computer Vision and Pattern Recognition}. 1–8.PDF icon Kienzle et al._2006_Learning an Interest Operator from Human Eye Movements.pdf (1.41 MB)
Kienzle, W., Wichmann F. A., Schölkopf B., & Franz M. O. (2006).  Learning eye movements. {Proc. Sensory Coding and the Natural Environment 2006}.
Kienzle, W., Wichmann F. A., Schölkopf B., & Franz M. O. (2007).  Learning the influence of spatio-temporal variations in local image structure on visual saliency. (Bülthoff, H. H., Chatziastros A., Mallot H. A., & Ulrich R., Ed.).{Proc. 10. Tübinger Wahr\-neh\-mungs\-konferenz (TWK 2007)}. 63.
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Bobach, T., & Umlauf G. (2006).  Natural neighbor interpolation and order of continuity. (Hagen, H., Kerren A., & Dannenmann P., Ed.).GI Lecture Notes in Informatics, Visualization of Large and Unstructured Data Sets. PDF icon NatNeighborInterp.pdf (1.47 MB)

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