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Philip Haeusser
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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
4826*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
28122016
Associative Domain Adaptation
P Haeusser, T Frerix, A Mordvintsev, D Cremers
In IEEE International Conference on Computer Vision (ICCV), 2017
2922017
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
198*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
1452017
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
1322019
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
192015
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
112021
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
92017
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
72023
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
62022
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
52022
Golkov,“
A Dosovitskiy, P Fischer, E Ilg, P Häusser, C Hazirbas
FlowNet: Learning Optical Flow with Convolutional Networks,” in ICCV 2, 2015
42015
Methods, systems, devices, and components for visualizing electrographic flow (EGF)
DE Lukŝic, P Haeusser, P Ruppersberg
US Patent 11,672,465, 2023
32023
Learning by association
P Häusser, A Mordvintsev, D Cremers
Doctoral dissertation, Technische Universität München, 2018
22018
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
Systems, Devices, Components and Methods for Detecting the Locations of Sources of Cardiac Rhythm Disorders in a Patient's Heart Using Improved Electrographic Flow (EGF) Methods
P Haeusser, P Ruppersberg, C Dinh
US Patent App. 17/571,496, 2022
2022
Biosignal-Based Intracardiac Navigation Systems, Devices, Components and Methods
SM Denner, P Haeusser, P Ruppersberg, DE Luksic, AT Grund
US Patent App. 17/863,246, 2022
2022
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