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D. Uttenweiler, Veigel, C., Steubing, R., Götz, C., Mann, S., Haußecker, H., Jähne, B., and Fink, R. H. A., “Motion determination in actin filament fluorescence images with a spatio-temporal orientation analysis method.”, Biophys J, vol. 78, p. 2709--2715, 2000.
D. Uttenweiler, Weber, C., Jähne, B., Fink, R. H. A., and Schaar, H., “Spatiotemporal anisotropic diffusion filtering to improve signal-to-noise ratios and object restoration in fluorescence microscopic image sequences.”, J Biomed Opt, vol. 8, p. 40--47, 2003.
G. Urban, “Neural Networks: Optimization and Applications”, University of Heidelberg, 2014.
G. Urban, Bendszus, M., Hamprecht, F. A., and Kleesiek, J., “Multi-modal Brain Tumor Segmentation using Deep Convolutional NeuralNetworks”, in MICCAI BraTS (Brain Tumor Segmentation) Challenge. Proceedings, winningcontribution, 2014, pp. 31-35.
V. Ulman, Maška, M., Magnusson, K. E. G., Ronneberger, O., Haubold, C., Harder, N., Matula, P., Matula, P., Svoboda, D., Radojevic, M., Smal, I., Rohr, K., Jaldén, J., Blau, H. M., Dzyubachyk, O., Lelieveldt, B., Xiao, P., Li, Y., Cho, S. - Y., Dufour, A., Olivo-Marin, J. C., Reyes-Aldasoro, C. C., Solis-Lemus, J. A., Bensch, R., Brox, T., Stegmaier, J., Mikut, R., Wolf, S., Hamprecht, F. A., Esteves, T., Quelhas, P., Demirel, Ö., Malström, L., Jug, F., Tomančák, P., Meijering, E., Muñoz-Barrutia, A., Kozubek, M., and Ortiz-de-Solorzano, C., “An Objective Comparison of Cell Tracking Algorithms”, Nature Methods, vol. 14, no. 12, pp. 1141-1152, 2017.PDF icon Technical Report (4.24 MB)
V. Uhlmann, Haubold, C., Hamprecht, F. A., and Unser, M., “Diverse Shortest Paths for Bioimage Analysis”, Bioinformatics, pp. 1-3, 2017.
N. Ufer and Ommer, B., “Deep Semantic Feature Matching”, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.PDF icon article (8.88 MB)
N. Ufer, Lui, K. To, Schwarz, K., Warkentin, P., and Ommer, B., “Weakly Supervised Learning of Dense SemanticCorrespondences and Segmentation”, in German Conference on Pattern Recognition (GCPR), 2019.PDF icon article (6.1 MB)
N. Ufer, Lang, S., and Ommer, B., “Object Retrieval and Localization in Large Art Collections Using Deep Multi-style Feature Fusion and Iterative Voting”, IEEE European Conference on Computer Vision (ECCV), VISART Workshop . 2020.PDF icon Paper (1.03 MB)