| Flownet: Learning optical flow with convolutional networks A Dosovitskiy, P Fischer, E Ilg, P Hausser, C Hazirbas, V Golkov, ... Proceedings of the IEEE international conference on computer vision, 2758-2766, 2015 | 5327* | 2015 |
| A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation N Mayer, E Ilg, P Hausser, P Fischer, D Cremers, A Dosovitskiy, T Brox Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 3217 | 2016 |
| Associative Domain Adaptation P Haeusser, T Frerix, A Mordvintsev, D Cremers In IEEE International Conference on Computer Vision (ICCV), 2017 | 302 | 2017 |
| Purcell-enhanced single-photon emission from nitrogen-vacancy centers coupled to a tunable microcavity H Kaupp, T Hümmer, M Mader, B Schlederer, J Benedikter, P Haeusser, ... Physical Review Applied 6 (5), 054010, 2016 | 212* | 2016 |
| Learning by Association - A versatile semi-supervised training method for neural networks P Häusser, A Mordvintsev, D Cremers IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 | 151 | 2017 |
| Associative deep clustering: Training a classification network with no labels P Haeusser, J Plapp, V Golkov, E Aljalbout, D Cremers Pattern Recognition: 40th German Conference, GCPR 2018, Stuttgart, Germany …, 2019 | 149 | 2019 |
| Smagt P. vd, Cremers D., and Brox T.,“ A Dosovitskiy, P Fischer, E Ilg, P Häusser, C Hazırbaş, V Golkov Flownet: Learning optical flow with convolutional networks,” in 2015 IEEE …, 2015 | 18 | 2015 |
| Electrographic flow mapping for atrial fibrillation: theoretical basis and preliminary observations DE Haines, MH Kong, P Ruppersberg, P Haeusser, B Avitall, T Szili-Torok, ... Journal of Interventional Cardiac Electrophysiology 66 (4), 1015-1028, 2023 | 17 | 2023 |
| Functional electrographic flow patterns in patients with persistent atrial fibrillation predict outcome of catheter ablation T Szili‐Torok, Z Kis, R Bhagwandien, S Wijchers, SC Yap, M Hoogendijk, ... Journal of Cardiovascular Electrophysiology 32 (8), 2148-2158, 2021 | 15 | 2021 |
| Better text understanding through image-to-text transfer K Kurach, S Gelly, M Jastrzebski, P Haeusser, O Teytaud, D Vincent, ... arXiv preprint arXiv:1705.08386, 2017 | 9 | 2017 |
| Systems, devices, components and methods for detecting the locations of sources of cardiac rhythm disorders in a patient's heart P Haeusser, P Ruppersberg US Patent 11,484,239, 2022 | 8 | 2022 |
| Systems, devices, components and methods for detecting the locations of sources of cardiac rhythm disorders in a patient's heart P Haeusser, P Ruppersberg US Patent 11,389,102, 2022 | 7 | 2022 |
| Methods, systems, devices, and components for visualizing electrographic flow (EGF) DE Lukŝic, P Haeusser, P Ruppersberg US Patent 11,672,465, 2023 | 5 | 2023 |
| Golkov,“ A Dosovitskiy, P Fischer, E Ilg, P Häusser, C Hazirbas FlowNet: Learning Optical Flow with Convolutional Networks,” in ICCV 2, 2015 | 3 | 2015 |
| Learning by association P Häusser, A Mordvintsev, D Cremers Doctoral dissertation, Technische Universität München, 2018 | 2 | 2018 |
| Systems, Devices, Components and Methods for Detecting the Locations of Sources of Cardiac Rhythm Disorders in a Patient's Heart Using Body Surface Electrodes and/or Cardiac … P Haeusser, P Ruppersberg, MHSM Kong, JV Koblish US Patent App. 17/499,807, 2022 | 1 | 2022 |
| Superresolution in the heart-Spatio-temporal activation wavefront reconstruction from sparsely sampled electrograms K Ahapov, P Ruppersberg, P Haeusser, MH Kong, M Moeller | | 2024 |
| Systems, Devices, Components and Methods for Electroanatomical Mapping of the Heart Using 3D Reconstructions Derived from Biosignals AT Grund, SM Denner, DE Luksic, P Haeusser, P Ruppersberg, ... US Patent App. 18/125,630, 2023 | | 2023 |
| PO-02-189 ATRIAL ARRHYTHMIA PREDICTION USING ELECTROGRAPHIC FLOW MAPPING METRICS JD Hummel, S Castellano, P Haeusser, MH Kong Heart Rhythm 20 (5), S304, 2023 | | 2023 |
| Methods, Systems, Devices, and Components for Extracting Atrial Signals from QRS and QRST Complexes L Tenbrink, P Haeusser, P Ruppersberg US Patent App. 17/831,249, 2023 | | 2023 |
Daniel CremersTechnical University of MunichVerified email at tum.de
