Publications
2021
Schütz, L M, Louveaux, M, Vilches-Barro, A, Bouziri, S, Cerrone, L, Wolny, A, Kreshuk, A, Hamprecht, F A and Maizel, A (2021).
Integration of Cell Growth and Asymmetric Division during Lateral Root Initiation in Arabidopsis thaliana.
Plant and Cell Physiology.
62 1269-1279
Pape, C, Remme, R, Wolny, A, Olberg, S, Wolf, S, Cerrone, L, Cortese, M, Klaus, S, Lucic, B, Ullrich, S, Anders-Össwein, M, Wolf, S, Cerikan, B, Neufeldt, C J, Ganter, M, Schnitzler, P, Merle, U, Lusic, M, Boulant, S, Stanifer, M, Bartenschlager, R, Hamprecht, F A, Kreshuk, A, Tischer, C, Kräusslich, H - G, Müller, B and Laketa, V (2021).
Microscopy-based assay for semi-quantitative detection of SARS-CoV-2 specific antibodies in human sera.
BioEssays.
43 Pape, C, Remme, R, Wolny, A, Olberg, S, Wolf, S, Cerrone, L, Cortese, M, Klaus, S, Lucic, B, Ullrich, S, Anders-Össwein, M, Wolf, S, Cerikan, B, Neufeldt, C J, Ganter, M, Schnitzler, P, Merle, U, Lusic, M, Boulant, S, Stanifer, M, Bartenschlager, R, Hamprecht, F A, Kreshuk, A, Tischer, C, Kräusslich, H - G, Müller, B and Laketa, V (2021).
Microscopy-based assay for semi-quantitative detection of SARS-CoV-2 specific antibodies in human sera.
BioEssays.
43 Islam, M Amirul, Kowal, M, Esser, P, Jia, S, Ommer, B, Derpanis, K G and Bruce, N (2021).
Shape or Texture: Understanding Discriminative Features in CNNs.
International Conference on Learning Representations (ICLR) Dorkenwald, M, Milbich, T, Blattmann, A, Rombach, R, Derpanis, K G and Ommer, B (2021).
Stochastic Image-to-Video Synthesis usin cINNs.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Brattoli, B, Büchler, U, Dorkenwald, M, Reiser, P, Filli, L, Helmchen, F, Wahl, A - S and Ommer, B (2021).
Unsupervised behaviour analysis and magnification (uBAM) using deep learning.
Nature Machine Intelligence.
https://rdcu.be/ch6pL Brattoli, B, Büchler, U, Dorkenwald, M, Reiser, P, Filli, L, Helmchen, F, Wahl, A - S and Ommer, B (2021).
Unsupervised behaviour analysis and magnification (uBAM) using deep learning.
Nature Machine Intelligence.
https://rdcu.be/ch6pL 2020
Wolny, A, Cerrone, L, Vijayan, A, Tofanelli, R, Vilches-Barro, A, Louveaux, M, Wenzel, C, Strauss, S, Wilson-Sanchez, D, Lymbouridou, R, Steigleder, S S, Pape, C, Bailoni, A, Duran-Nebreda, S, Bassel, G W, Lohmann, J U, Tsiantis, M, Hamprecht, F A, Schneitz, K, Maizel, A and Kreshuk, A (2020).
Accurate and Versatile 3D Segmentation of Plant Tissues at Cellular Resolution.
eLife.
9 Wolny, A, Cerrone, L, Vijayan, A, Tofanelli, R, Vilches-Barro, A, Louveaux, M, Wenzel, C, Strauss, S, Wilson-Sanchez, D, Lymbouridou, R, Steigleder, S S, Pape, C, Bailoni, A, Duran-Nebreda, S, Bassel, G W, Lohmann, J U, Tsiantis, M, Hamprecht, F A, Schneitz, K, Maizel, A and Kreshuk, A (2020).
Accurate and Versatile 3D Segmentation of Plant Tissues at Cellular Resolution.
eLife.
9 Kluger, F, Brachmann, E, Ackermann, H, Rother, C, Yang, M Ying and Rosenhahn, B (2020).
CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus.
CVPR 2020.
http://arxiv.org/abs/2001.02643 PDF (9.95 MB) Bollweg, S, Haußmann, M, Kasieczka, G, Luchmann, M, Plehn, T and Thompson, J (2020).
Deep-Learning Jets with Uncertainties and More.
SciPost Phys.
8.
https://scipost.org/10.21468/SciPostPhys.8.1.006 Technical Report (1.65 MB) Milbich, T, Roth, K, Bharadhwaj, H, Sinha, S, Bengio, Y, Ommer, B and Cohen, J Paul (2020).
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning.
IEEE European Conference on Computer Vision (ECCV).
https://arxiv.org/abs/2004.13458 Milbich, T, Roth, K, Bharadhwaj, H, Sinha, S, Bengio, Y, Ommer, B and Cohen, J Paul (2020).
DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning.
IEEE European Conference on Computer Vision (ECCV).
https://arxiv.org/abs/2004.13458 Schilling, H, Gutsche, M, Brock, A, Späth, D, Rother, C and Krispin, K (2020).
Mind the Gap – A Benchmark for Dense Depth Prediction beyond Lidar.
2nd Workshop on Safe Artificial Intelligence for Automated Driving, in conjunction with CVPR 2020 Wolf, S, Bailoni, A, Pape, C, Rahaman, N, Kreshuk, A, Köthe, U and Hamprecht, F A (2020).
The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning.
IEEE Transactions on Pattern Analysis and Machine Intelligence.
43 3724-3738
Technical Report (2.58 MB) Wolf, S, Li, Y, Pape, C, Bailoni, A, Kreshuk, A and Hamprecht, F A (2020).
The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation.
ECCV. Proceedings. 208-224
Dorkenwald, M, Büchler, U and Ommer, B (2020).
Unsupervised Magnification of Posture Deviations Across Subjects.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) article.pdf (1.15 MB) 2019
Jähne, (2019).
Air-Sea Gas Exchange.
Encyclopedia of Ocean Sciences. Academic Press.
6 1–13
Bendinger, A L, Debus, C, Glowa, C, Karger, C P, Peter, J and Storath, M (2019).
Bolus arrival time estimation in dynamic contrast-enhanced magnetic resonance imaging of small animals based on spline models, in press.
Physics in Medicine and Biology.
64 Kleesiek, J, Morshuis, J Nikolas, Isensee, F, Deike-Hofmann, K, Paech, D, Kickingereder, P, Köthe, U, Rother, C, Forsting, M, Wick, W, Bendszus, M, Schlemmer, H Peter and Radbruch, A (2019).
Can Virtual Contrast Enhancement in Brain MRI Replace Gadolinium?: A Feasibility Study.
Investigative Radiology.
54 653–660
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