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Publications

Export 1965 results:
Author [ Title(Desc)] Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
D
B. Jähne, Digital Image Processing --- Concepts, Algorithms, and Scientific Applications, 3rd ed. Springer, 1995.
B. Jähne, Digital Image Processing --- Concepts, Algorithms, and Scientific Applications, 2nd ed. Springer, 1993.
B. Jähne, Digital Image Processing - Concepts, Algorithms, and Scientific Applications. Springer, 1991.
M. Kandemir, Feuchtinger, A., Walch, A., and Hamprecht, F. A., “Digital Pathology: Multiple instance learning can detect Barrett'scancer”, ISBI. Proceedings. pp. 1348-1351, 2014.PDF icon Technical Report (2.86 MB)
C. Rother, Kumar, S., Kolmogorov, V., and Blake, A., “Digital tapestry [automatic image synthesis]”, in Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, 2005, vol. 1, pp. 589–596.
B. Jähne, Digitale Bildverarbeitung, 6th ed. Springer, 2005.
B. Jähne, Digitale Bildverarbeitung, Fünfte. Springer Verlag, 2002.
B. Jähne, Digitale Bildverarbeitung, 4th ed. Springer, 1997.
B. Jähne, Digitale Bildverarbeitung, 3rd ed. Springer, 1993.
B. Jähne, Digitale Bildverarbeitung, 2nd ed. Springer, 1991.
B. Jähne, Digitale Bildverarbeitung. Springer, 1989.
B. Jähne, Digitale Bildverarbeitung und Bildgewinnung. Springer Vieweg, 2012.
H. Scharr, “Digitale Bildverarbeitung und Papier Texturanalyse mittels Pyramiden und Grauwertstatistiken am Beispiel der Papierformation”, IWR, Fakultät für Physik und Astronomie, Univ.\ Heidelberg, 1996.
M. Jehle, Jähne, B., and Kertzscher, U., “Direct estimation of the wall shear rate using parametric motion models in 3D”, in Proceedings of the 28th DAGM Symposium on Pattern Recognition, 2006, vol. 4174, p. 434--443.
E. Fita, Damrich, S., and Hamprecht, F. A., “Directed Probabilistic Watershed”, NeurIPS. Proceedings, vol. 34. 2021.PDF icon Technical Report (957.78 KB)
E. Kirschbaum, Bailoni, A., and Hamprecht, F. A., “DISCo: Deep Learning, Instance Segmentation, and Correlations for Cell Segmentation in Calcium Imaging”, MICCAI. Proceedings. pp. 151-162, 2020.
K. Lerch, “Discontinuity Preserving Filtering of Spectral Images”, University of Heidelberg, 2006.
A. Bruhn, Weickert, J., Kohlberger, T., and Schnörr, C., “Discontinuity-Preserving Computation of Variational Optic Flow in Real-Time”, in Scale-Space 2005, 2005, vol. 3459, pp. 279–290.
S. Damrich, “Discovering Structure without Labels”, Heidelberg University. 2022.
J. Lellmann, Lellmann, B., Widmann, F., and Schnörr, C., “Discrete and Continuous Models for Partitioning Problems”, Int.~J.~Comp.~Visionz, vol. 104, pp. 241-269, 2013.PDF icon Technical Report (4.74 MB)
B. X. Kausler, Schiegg, M., Andres, B., Lindner, M., Köthe, U., Leitte, H., Wittbrodt, J., Hufnagel, L., and Hamprecht, F. A., “A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness”, in ECCV 2012. Proceedings, 2012, vol. 7574, pp. 144-157.PDF icon Technical Report (809.07 KB)
B. Savchynskyy, “Discrete Graphical Models — An Optimization Perspective”, Foundations and Trends® in Computer Graphics and Vision, vol. 11, pp. 160–429, 2019.
J. Yuan, Schnörr, C., and Mémin, E., “Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation”, J.~Math.~Imag.~Vision, vol. 28, pp. 67-80, 2007.PDF icon Technical Report (752.44 KB)
J. Yuan, Ruhnau, P., Mémin, E., and Schnörr, C., “Discrete Orthogonal Decomposition and Variational Fluid Flow Estimation”, in Scale-Space 2005, 2005, vol. 3459, pp. 267–278.
M. Zisler, Petra, S., Schnörr, C., and Schnörr, C., “Discrete Tomography by Continuous Multilabeling Subject to Projection Constraints”, in Proc. GCPR, 2016.
T. Schüle, Schnörr, C., Weber, S., and Hornegger, J., “Discrete Tomography By Convex-Concave Regularization and D.C. Programming”, Discr. Appl. Math., vol. 151, pp. 229-243, 2005.
T. Schüle, Schnörr, C., Weber, S., and Hornegger, J., “Discrete Tomography By Convex-Concave Regularization and D.C. Programming”, Dept. Math. and Comp. Science, University of Mannheim, Germany, 15, 2003.
U. Schmidt, Rother, C., Nowozin, S., Jancsary, J., and Roth, S., “Discriminative Non-blind Deblurring”, 2013.
P. Sorrenson, Rother, C., and Köthe, U., “Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)”, in Intl. Conf. Learning Representations (ICLR), 2020.PDF icon PDF (2.43 MB)
P. Esser, Rombach, R., and Ommer, B., “A Disentangling Invertible Interpretation Network for Explaining Latent Representations”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2020.PDF icon Article (13.07 MB)
A. Stahl, Ruhnau, P., and Schnörr, C., “A Distributed Parameter Approach to Dynamic Image Motion”, in ECCV 2006, International Workshop on The Representation and Use of Prior Knowledge in Vision, 2006.PDF icon Technical Report (1.24 MB)
T. Milbich, Roth, K., Bharadhwaj, H., Sinha, S., Bengio, Y., Ommer, B., and Cohen, J. Paul, “DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning”, IEEE European Conference on Computer Vision (ECCV). 2020.
C. Haubold, Uhlmann, V., Unser, M., and Hamprecht, F. A., “Diverse M-best Solutions by Dynamic Programming”, GCPR. Proceedings, vol. LNCS 10496. Springer, pp. 255-267, 2017.
V. Uhlmann, Haubold, C., Hamprecht, F. A., and Unser, M., “Diverse Shortest Paths for Bioimage Analysis”, Bioinformatics, pp. 1-3, 2017.
A. Sanakoyeu, Tschernezki, V., Büchler, U., and Ommer, B., “Divide and Conquer the Embedding Space for Metric Learning”, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2019.

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