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2010
Z. Lin, Erz, M., and Jähne, B., “Multi-frequency multi-sampling fluorescence lifetime imaging using a high-speed line-scan camera”, in Optics, Photonics, and Digital Technologies for Multimedia Applications, 12--15 April 2010, Brussels, 2010, vol. 7723, p. 77231S.
R. Chellappa and Machinery., Afor Comput, “Proceedings - 7th Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2010”, ACM International Conference Proceeding Series. ACM, 2010.
P. Yarlagadda, Monroy, A., Carque, B., and Ommer, B., “Recognition and Analysis of Objects in Medieval Images”, in Proceedins of the Aian Conference on Computer Vision, Workshop on e-Heritage, 2010, p. 296--305.PDF icon Technical Report (2.76 MB)
A. Berthe, Kondermann, D., Christensen, C., Goubergrits, L., Garbe, C. S., Affeld, K., and Kertzscher, U., “Three-dimensional, three-component wall-PIV”, Exp. Fluids, vol. 48, p. online, 2010.
2011
A. Kreshuk, Straehle, C. N., Sommer, C., Köthe, U., Cantoni, M., Knott, G. W., and Hamprecht, F. A., “Automated Detection and Segmentation of Synaptic Contacts in Nearly Isotropic Serial Electron Microscopy Images”, PLoS ONE, vol. 6 (10), 2011.PDF icon Technical Report (290.48 KB)
F. O. Kaster, Weber, M. - A., and Hamprecht, F. A., “Comparative Validation of Graphical Models for Learning Tumor Segmentations from Noisy Manual Annotations”, in LNCS, 2011, vol. LNCS 6533, pp. 74-85.PDF icon Technical Report (544.56 KB)
J. Schlecht, Carque, B., and Ommer, B., “Detecting Gestures in Medieval Images”, in Proceedings of the International Conference on Image Processing, 2011, p. 1309--1312.PDF icon Technical Report (1.61 MB)
E. Töppe, Oswald, M. R., Cremers, D., and Rother, C., “Image-based 3D modeling via cheeger sets”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2011, vol. 6492 LNCS, pp. 53–64.
A. Monroy, Carque, B., and Ommer, B., “Reconstructing the Drawing Process of Reproductions from Medieval Images”, in Proceedings of the International Conference on Image Processing, 2011, p. 2974--2977.PDF icon Technical Report (2.43 MB)
P. Yarlagadda, Monroy, A., Carque, B., and Ommer, B., “Top-down Analysis of Low-level Object Relatedness Leading to Semantic Understanding of Medieval Image Collections”, in Conference on Computer Vision and Image Analysis of Art II, 2011, vol. 7869, p. 61--69.PDF icon Technical Report (11.06 MB)
2012
J. Funke, Andres, B., Hamprecht, F. A., Cardona, A., and Cook, M., “Efficient Automatic 3D-Reconstruction of Branching Neurons from EM Data”, CVPR 2012. Proceedings, pp. 1004-1011, 2012.PDF icon Technical Report (1.64 MB)
J. Funke, Andres, B., Hamprecht, F. A., Cardona, A., and Cook, M., “Efficient Automatic 3D-Reconstruction of Branching Neurons from EM Data”, CVPR 2012. Proceedings, pp. 1004-1011, 2012.PDF icon Technical Report (1.64 MB)
B. Goldlücke, Strekalovskiy, E., and Cremers, D., “The Natural Vectorial Total Variation which Arises from Geometric Measure Theory”, SIAM Journal on Imaging Sciences, vol. 5, pp. 537-563, 2012.
B. Goldlücke, Strekalovskiy, E., and Cremers, D., “The natural vectorial total variation which arises from geometric measure theory”, SIAM Journal on Imaging Sciences, 2012.
2013
B. Maco, Holtmaat, A., Cantoni, M., Kreshuk, A., Straehle, C. N., Hamprecht, F. A., and Knott, G. W., “Correlative in vivo 2 photon and focused ion beam scanning electron microscopy of cortical neurons”, PloS one, vol. 8 (2), 2013.PDF icon Technical Report (2.13 MB)
D. Lefloch, Nair, R., Lenzen, F., Schäfer, H., Streeter, L., and Cree, M. J., “Technical Foundation and Calibration Methods for Time-of-Flight Cameras”, in Time-of-Flight Imaging: Algorithms, Sensors and Applications, 2013, vol. 8200.
D. Lefloch, Nair, R., Lenzen, F., Schäfer, H., Streeter, L., Cree, M. J., Koch, R., and Kolb, A., “Technical Foundation and Calibration Methods for Time-of-Flight Cameras”, Time-of-Flight and Depth Imaging: Sensors, Algorithms, and Applications, vol. 8200. Springer, pp. 3-24, 2013.
B. Goldlücke, Strekalovskiy, E., and Cremers, D., “Tight convex relaxations for vector-valued labeling”, SIAM Journal on Imaging Sciences, 2013.
P. Yarlagadda, Monroy, A., Carque, B., and Ommer, B., “Towards a Computer-based Understanding of Medieval Images”, in Scientific Computing & Cultural Heritage, Springer, 2013, p. 89--97.
2014
A. - S. Wahl, Omlor, W., Rubio, J. C., Chen, J. L., Zheng, H., Schröter, A., Gullo, M., Weinmann, O., Kobayashi, K., Helmchen, F., Ommer, B., and Schwab, M. E., “Asynchronous Therapy Restores Motor Control by Rewiring of the Rat Corticospinal Tract after Stroke”, Science, vol. 344, p. 1250--1255, 2014.
S. Zheng, Cheng, M. Ming, Warrell, J., Sturgess, P., Vineet, V., Rother, C., and Torr, P. H. S., “Dense semantic image segmentation with objects and attributes”, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2014, pp. 3214–3221.
B. Maco, Cantoni, M., Holtmaat, A., Kreshuk, A., Hamprecht, F. A., and Knott, G. W., “Semiautomated Correlative 3D Electron Microscopy of In Vivo Imaged Axons and Dendrites”, Nature Protocols, vol. 9, pp. 1354-1366, 2014.PDF icon Technical Report (2.01 MB)
B. Goldlücke, Aubry, M., Kolev, K., and Cremers, D., “A super-resolution framework for high-accuracy multiview reconstruction”, Int. J. Comp. Vision, vol. 106, p. 172--191, 2014.
2015
S. Zheng, Prisacariu, V. Adrian, Averkiou, M., Cheng, M. Ming, Mitra, N. J., Shotton, J., Torr, P. H. S., and Rother, C., “Object proposals estimation in depth image using compact 3D shape manifolds”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, vol. 9358, pp. 196–208.
N. J. Mitra, Stam, J., Xu, K., Cheng, M. - M., Prisacariu, V. Adrian, Zheng, S., Torr, P. H. S., and Rother, C., “Pacific Graphics 2015 DenseCut: Densely Connected CRFs for Realtime GrabCut”, vol. 34, 2015.
C. Cali, Baghabra, J., Boges, D. J., Holst, G. R., Kreshuk, A., Hamprecht, F. A., Srinivasan, M., Lehväslaiho, H., and Magistretti, P. J., “Three-dimensional immersive virtual reality for studying cellular compartments in 3D models from EM preparations of neural tissues”, Journal of Comparative Neurology, vol. 524, pp. 23-38, 2015.
D. Kiefhaber, Caulliez, G., Zappa, C. J., Schaper, J., and Jähne, B., “Water wave measurement from stereo images of specular reflections”, vol. 26, p. 115401, 2015.
A. Kreshuk, Funke, J., Cardona, A., and Hamprecht, F. A., “Who is talking to whom: synaptic partner detection in anisotropic volumes of insect brain”, MICCAI. Proceedings, vol. LNCS 9349. Springer, pp. 661-668, 2015.PDF icon Technical Report (2.14 MB)
2016
E. Meijering, Carpenter, A. E., Peng, H., Hamprecht, F. A., and Olivo-Marin, J., “Imagining the future of bioimage analysis”, Nature Biotechnology, vol. 34, no. 12, pp. 1250-1255, 2016.PDF icon Technical Report (924.57 KB)
Y. Censor, Gibali, A., Lenzen, F., and Schnörr, C., “The Implicit Convex Feasibility Problem and Its Application to Adaptive Image Denoising”, J. Comp. Math., vol. 34, pp. 608-623, 2016.
2017
T. Beier, Pape, C., Rahaman, N., Prange, T., Berg, S., Bock, D., Cardona, A., Knott, G. W., Plaza, S. M., Scheffer, L. K., Köthe, U., Kreshuk, A., and Hamprecht, F. A., “Multicut brings automated neurite segmentation closer to human performance”, Nature Methods, vol. 14, no. 2, pp. 101-102, 2017.
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)
S. Peter, Kirschbaum, E., Both, M., Campbell, L. A., Harvey, B. K., Heins, C., Durstewitz, D., Diego, F., and Hamprecht, F. A., “Sparse convolutional coding for neuronal assembly detection”, NIPS, poster. 2017.
2018
L. Cerrone, “Deep End-to-End Learning of a Diffusion Process for Seeded Image Segmentation”, Heidelberg University, 2018.
N. Rahaman, Arpit, D., Baratin, A., Draxler, F., Lin, M., Hamprecht, F. A., Bengio, Y., and Courville, A., “On the spectral bias of deep neural networks”, arXiv preprint arXiv:1806.08734, 2018.

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