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Neigel, P (2017). Self-Similarity Based Detection Of Temporal Motifs In Multivariate Signals. Heidelberg University
Staudacher, M, Hamprecht, F A and Görlitz, L (2009). Self Adjustment of Scanning Electron Microscopes / Selbstadaptivität von Rasterelektronenmikroskopen. Patent, Patent Number WO2009062781A1PDF icon Technical Report (46.64 KB)
Andres, B, Hamprecht, F A and Garbe, C S (2007). Selection of Local Optical Flow Models by Means of Residual Analysis. Pattern Recognition. Springer. 4713 72-81PDF icon Technical Report (229.64 KB)
Andres, B, Garbe, C S, Schnörr, C and Jähne, B (2007). Selection of local optical flow models by means of residual analysis. Proceedings of the 29th DAGM Symposium on Pattern Recognition. Springer. 72--81
Jähne, (1998). Sehen, was man sonst nicht sieht. Ruperto Carola. 32--36.
Haubold, C, Schiegg, M, Kreshuk, A, Berg, S, Köthe, U and Hamprecht, F A (2016). Segmenting and Tracking Multiple Dividing Targets Using ilastik. Focus on Bio-Image Informatics. Springer. 219 199-229PDF icon Technical Report (4.46 MB)
Leue, C, Geißler, P, Jähne, B, Jähne, B, Geißler, P and Haußecker, H (1996). Segmentierung von Partikelbildern in der Strömungsvisualisierung. Proceedings of 18th DAGM-Symposium Mustererkennung. 118--129
Schnörr, (1994). Segmentation of Visual Motion by Minimizing Convex Non-Quadratic Functionals. 12th Int. Conf. on Pattern Recognition
Andres, B, Köthe, U, Helmstaedter, M, Denk, W and Hamprecht, F A (2008). Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification. Pattern Recognition. 30th DAGM Symposium Munich, Germany, June 10-13, 2008. Proceedings. Springer. 5096 142-152PDF icon Technical Report (1.21 MB)
Ommer, B (2008). Seeing The Objects Behind The Parts: Learning Compositional Models For Visual Recognition. VDM Verlag.
Ommer, B, Mader, T and Buhmann, J M (2009). Seeing the Objects Behind the Dots: Recognition in Videos from a Moving Camera. International Journal of Computer Vision. Springer. 83 57--71PDF icon Technical Report (9.61 MB)
Straehle, C, Köthe, U, Briggman, K, Denk, W and Hamprecht, F A (2012). Seeded watershed cut uncertainty estimators for guided interactive segmentation. CVPR 2012. Proceedings. 765 - 772PDF icon Technical Report (2.84 MB)
Berger, J, Lenzen, F, Becker, F, Neufeld, A and Schnörr, C (2015). Second-Order Recursive Filtering on the Rigid-Motion Lie Group SE(3) Based on Nonlinear Observations. icon Technical Report (4.42 MB)
Berger, J, Neufeld, A, Becker, F, Lenzen, F and Schnörr, C (2015). Second Order Minimum Energy Filtering on SE(3) with Nonlinear Measurement Equations. Scale Space and Variational Methods in Computer Vision (SSVM 2015). Springer International Publishing. icon Technical Report (364.01 KB)
Görlitz, L, Singh, M and Schützbach, P (2007). Schnelle 3D-Vermessung von Partikeln in Rasterelektronenmiskroskopen mit Hilfe eines Rücksteuerdetektors
Richter, K E, Rocholz, R and Jähne, B (2012). The Schmidt Number Dependency of Air-Sea Gas Exchange with Varying Surfactant Coverage. SOLAS Open Science Conference, Washington State, USA
Geese, M, Ruhnau, P and Jähne, B (2012). Scene based maximum likelihood PRNU and DSNU non uniformity correction. Forum Bildverarbeitung. KIT Scientific Publishing. 71--82.
Haubold, C (2017). Scalable Inference for Multi-Target Tracking on Proliferating Cells. University of Heidelberg
Friedrich, O, Weber, C, Both, M, von Wegner, F, Chamberlain, J S, Garbe, C S and Fink, R H A (2008). Sarcomere Structure and Motor-Protein Function in an Animal Model of Duchenne Muscular Dystrophy (mdx mouse). 87th Annual Meeting of the German Physiological Society
Haußmann, M, Hamprecht, F A and Kandemir, M (2019). Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation. UAI. Proceedings, in press
Andres, B, Köthe, U, Kröger, T and Hamprecht, F A (2010). Runtime-Flexible Multi-dimensional Views and Arrays for C++98 and C++0x. ArXiv e-prints. icon Technical Report (415.54 KB)
Kirchgeßner, N, Spies, H, Scharr, H and Schurr, U (2001). Root Growth Measurements in Object Coordinates. Proceedings of the 23th DAGM Symposium on Pattern Recognition. Springer
Kirchgeßner, N, Spies, H, Scharr, H and Schurr, U (2001). Root Growth Analysis in Physiological Coordinates. International Conference on Image Analysis and Processing (ICIAP'01)
Ommer, B (2013). The Role of Shape in Visual Recognition. Shape Perception in Human Computer Vision: An Interdisciplinary Perspective. Springer. 373--385PDF icon Technical Report (8.18 MB)
Jähne, B, Haußecker, H, Hering, F, Balschbach, G, Klinke, J, Lell, M, Schmund, D, Schultz, M, Schurr, U, Stitt, M and Platt, U (1996). The role of active vision in exploring growth, transport, and exchange processes. Aktives Sehen in technischen und biologischen Systemen, Workshop der GI-Fachgruppe 1.0.4. Bildverstehen Hamburg, 3--4. December 1996. infix. 4 194--202
Hering, F, Merle, M, Wierzimok, D and Jähne, B (1995). A robust technique for tracking particles over long image sequences. Proc. ISPRS Intercommission Workshop `From Pixels to Sequences', Zurich, March 22 - 24, 1995, In Int'l Arch. of Photog. and Rem. Sens. RISC Books. XXX-5W1 74--79
Li, J (2019). Robust Single Object Tracking Via Fully Convolutional Siamese Networks. Heidelberg University
König, T, Menze, B H, Kirchner, M, Monigatti, F, Parker, K C, Patterson, T, J. Steen, J, Hamprecht, F A and Steen, H (2008). Robust Prediction of the MASCOT Score for an Improved Quality Assessment in Mass Spectrometric Proteomics. Journal of Proteome Research. 7 3708-3717PDF icon Technical Report (1.16 MB)
Antic, B and Ommer, B (2012). Robust Multiple-Instance Learning with Superbags. Proceedings of the Aian Conference on Computer Vision (ACCV) (Oral). Springer. 242--255PDF icon Technical Report (319.58 KB)
Renard, B (2010). Robust Methods for the Proteomic Data Analysis Pipeline. University of Heidelberg
Breitenreicher, D and Schnörr, C (2010). Robust 3D object registration without explicit correspondence using geometric integration. Machine Vision and Applications. 21 601-611. icon Technical Report (1.65 MB)
Álvarez, J M, Gevers, T, Diego, F and López, A M (2012). Road Geometry Classification by Adaptive Shape Models. IEEE Transactions on Intelligent Transportation Systems (ITS). 99 1-10
Heiler, M and Schnörr, C (2005). Reverse-Convex Programming for Sparse Image Codes. Proc.~Int.~Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'05). Springer. 3757 600-616
Leue, C, Wenig, M, Platt, U, Jähne, B, Geißler, P and Haußecker, H (1999). Retrieval of Atmospheric Trace Gas Concentrations. Handbook of Computer Vision and Applications. Academic Press. 3: Systems and Applications 783-805
Wenig, M, Kuhl, S, Beirle, S, Bucsela, E, Jähne, B, Platt, U, Gleason, J and Wagner, T (2004). Retrieval and analysis of stratospheric NO$_2$ from the Global Ozone Monitoring Experiment. J. Geophys. Res. 109 D04315, 1--11